#Health APIs

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[jcmarchi]

Agentic AI: How Large Language Models Are Shaping the Future of Autonomous Agents

New Post has been published on https://thedigitalinsider.com/agentic-ai-how-large-language-models-are-shaping-the-future-of-autonomous-agents/

Agentic AI: How Large Language Models Are Shaping the Future of Autonomous Agents

After the rise of generative AI, artificial intelligence is on the brink of another significant transformation with the advent of agentic AI. This change is driven by the evolution of Large Language Models (LLMs) into active, decision-making entities. These models are no longer limited to generating human-like text; they are gaining the ability to reason, plan, tool-using, and autonomously execute complex tasks. This evolution brings a new era of AI technology, redefining how we interact with and utilize AI across various industries. In this article, we will explore how LLMs are shaping the future of autonomous agents and the possibilities that lie ahead.

The Rise of Agentic AI: What Is It?

Agentic AI refers to systems or agents that can independently perform tasks, make decisions, and adapt to changing situations. These agents possess a level of agency, meaning they can act independently based on goals, instructions, or feedback, all without constant human guidance.

Unlike conventional AI systems limited to fixed tasks, agentic AI is dynamic. It learns from interactions and improves its behavior over time. A essential feature of agentic AI is its ability to break down tasks into smaller steps, analyze different solutions, and make decisions based on various factors.

For instance, an AI agent planning a vacation could assess the weather, budget, and user preferences to recommend the best tour options. It can consult external tools, adjust suggestions based on feedback, and refine its recommendations over time. Applications for agentic AI span from virtual assistants managing complex tasks to industrial robots adapting to new production conditions.

The Evolution from Language Models to Agents

Traditional LLMs are powerful tools for processing and generating text, but they primarily function as advanced pattern recognition systems. Recent advancements have transformed these models, equipping them with capabilities that extend beyond simple text generation. They now excel in advanced reasoning and practical tool usage.

These models can formulate and execute multi-step plans, learn from past experiences, and make context-driven decisions while interacting with external tools and APIs. With the addition of long-term memory, they can retain context over extended periods, making their responses more adaptive and meaningful.

Together, these abilities have opened new possibilities in task automation, decision-making, and personalized user interactions, triggering a new era of autonomous agents.

The Role of LLMs in Agentic AI

Agentic AI relies on several core components facilitating interaction, autonomy, decision-making, and adaptability. This section explores how LLMs are driving the next generation of autonomous agents.

LLMs for Understanding Complex Instructions

For agentic AI, the ability to understand complex instructions is crucial. Traditional AI systems often require precise commands and structured inputs, limiting user interaction. LLMs, however, allow users to communicate in natural language. For example, a user can say, “Book a flight to New York and arrange accommodation near Central Park.” LLMs grasp this request by interpreting location, preferences, and logistics nuances. The AI can then carry out each task—from booking flights to selecting hotels and arranging tickets—while requiring minimal human oversight.

LLMs as Planning and Reasoning Frameworks

A key feature of agentic AI is its ability to break down complex tasks into smaller, manageable steps. This systematic approach is vital for solving more significant problems effectively. LLMs have developed planning and reasoning capabilities that empower agents to perform multi-step tasks, much like we do when solving math problems. Think of these capabilities as the “thinking process” of AI agents.

Techniques such as chain-of-thought (CoT) reasoning have emerged to help LLMs achieve these tasks. For example, consider an AI agent assisting a family save money on groceries. CoT allows LLMs to approach this task sequentially, following these steps:

Assess the family’s current grocery spending.

Identify frequent purchases.

Research sales and discounts.

Explore alternative stores.

Suggest meal planning.

Evaluate bulk purchasing options.

This structured method enables the AI to process information systematically, like how a financial advisor would manage a budget. Such adaptability makes agentic AI suitable for various applications, from personal finance to project management. Beyond sequential planning, more sophisticated approaches further enhance LLMs’ reasoning and planning abilities, allowing them to tackle even more complex scenarios.

LLMs for Enhancing Tool Interaction

A significant advancement in agentic AI is the ability of LLMs to interact with external tools and APIs. This capability enables AI agents to perform tasks such as executing code and interpreting results, interacting with databases, interfacing with web services, and managing digital workflows. By incorporating these capabilities, LLMs have evolved from being passive processors of language to becoming active agents in practical, real-world applications.

Imagine an AI agent that can query databases, execute code, or manage inventory by interfacing with company systems. In a retail setting, this agent could autonomously automate order processing, analyze product demand, and adjust restocking schedules. This kind of integration expands the functionality of agentic AI, enabling LLMs to interact with the physical and digital world seamlessly.

LLMs for Memory and Context Management

Effective memory management is vital for agentic AI. It allows LLMs to retain and reference information during long-term interactions. Without memory, AI agents struggle with continuous tasks. They find it hard to maintain coherent dialogues and execute multi-step actions reliably.

To address this challenge, LLMs use different types of memory systems. Episodic memory helps agents recall specific past interactions, aiding in context retention. Semantic memory stores general knowledge, enhancing the AI’s reasoning and application of learned information across various tasks. Working memory allows LLMs to focus on current tasks, ensuring they can handle multi-step processes without losing sight of their overall goal.

These memory capabilities enable agentic AI to manage tasks that require ongoing context. They can adapt to user preferences and refine outputs based on past interactions. For instance, an AI health coach can track a user’s fitness progress and provide evolving recommendations based on recent workout data.

How Advancements in LLMs Will Empower Autonomous Agents

As LLMs continue to advance with interaction, reasoning, planning, and tool usage, agentic AI will become increasingly capable of autonomously handling complex tasks, adapting to dynamic environments, and collaborating effectively with humans across various domains. Some of the ways AI agents will prosper with the advancing abilities of LLMs are:

Expanding into Multimodal Interaction

With the growing multimodal capabilities of LLMs, agentic AI will engage with more than just text in the future. LLMs can now incorporate data from various sources, including images, videos, audio, and sensory inputs. This allows agents to interact more naturally with different environments. As a result, AI agents will be able to navigate complex scenarios, such as managing autonomous vehicles or responding to dynamic situations in healthcare.

Improved Reasoning Capabilities

As LLMs enhance their reasoning abilities, agentic AI will thrive in making informed choices in uncertain, data-rich environments. It will evaluate multiple factors and manage ambiguities effectively. This capability is essential in finance and diagnostics, where complex, data-driven decisions are critical. As LLMs grow more sophisticated, their reasoning skills will foster contextually aware and thoughtful decision-making across various applications.

Specialized Agentic AI for Industry

As LLMs progress with data processing and tool usage, we will see specialized agents designed for specific industries, including finance, healthcare, manufacturing, and logistics. These agents will handle complex tasks such as managing financial portfolios, monitoring patients in real-time, adjusting manufacturing processes precisely, and predicting supply chain needs. Each industry will benefit from agentic AI’s ability to analyze data, make informed decisions, and adapt to new information autonomously.

Multi-agent Systems

The progress of LLMs will significantly enhance multi-agent systems in agentic AI. These systems will comprise specialized agents collaborating to tackle complex tasks effectively. With LLMs’ advanced capabilities, each agent can focus on specific aspects while sharing insights seamlessly. This teamwork will lead to more efficient and accurate problem-solving as agents simultaneously manage different parts of a task. For example, one agent might monitor vital signs in healthcare while another analyzes medical records. This synergy will create a cohesive and responsive patient care system, ultimately improving outcomes and efficiency in various domains.

The Bottom Line

Large Language Models rapidly evolve from simple text processors to sophisticated agentic systems capable of autonomous action. The future of Agentic AI, powered by LLMs, holds tremendous potential to reshape industries, enhance human productivity, and introduce new efficiencies in daily life. As these systems mature, they promise a world where AI is not just a tool but a collaborative partner, helping us navigate complexities with a new level of autonomy and intelligence.

[go4whatsup]

Improve the efficiency of your healthcare communication with the WhatsApp Business API. Perfect for clinics, hospitals, and healthcare providers who want to offer better patient support and streamline operations. Inquire today to transform your patient communication.

Learn more : https://www.go4whatsup.com/industries/healthcare/

Get in touch - Enquire Now - IND +91-9667584436 / UAE +971545085552 Email - admin@go4whatsup.com

[amroselifescience]

The Secret to Superior Supplements: The Role of Dicalcium Phosphate

Enhancing Bioavailability: How Dicalcium Phosphate Boosts Absorption

According to the Dicalcium Phosphate Granules Suppliers, it is a key player in nutritional supplements due to its role in improving bioavailability. This mineral compound acts as a carrier that aids in the dissolution of vitamins and minerals within the digestive system, enhancing their absorption into the bloodstream. Its unique properties ensure that nutrients are more effectively utilized by the body, making supplements more potent. By facilitating better nutrient uptake, it ensures that each dose delivers maximum benefit, transforming ordinary supplements into powerful sources of essential nutrients.

Stability and Consistency: The Advantage of This Mineral Compound

A major benefit of Dicalcium Phosphate is its contribution to stability and consistency in supplements. As an excipient, it helps preserve the integrity of the formula over time, preventing degradation and ensuring even distribution of active ingredients. This stability is essential for maintaining supplement potency and delivering reliable health benefits with each use. Incorporating this compound allows manufacturers to create high-quality products that remain effective throughout their shelf life, providing dependable nutritional support. Dicalcium Phosphate Granules for Sale.

Formulation Flexibility: Transforming Supplement Design

This mineral compound offers exceptional flexibility in supplement formulation, enabling the creation of a wide range of products. Its compatibility with various active ingredients supports the development of tablets, capsules, and powders. This versatility not only expands the options available to consumers but also allows for the inclusion of multiple nutrients in a single product. By leveraging its properties, manufacturers can design innovative formulations that address specific health needs and preferences, delivering tailored solutions for optimal nutrition. Dicalcium Phosphate Granules Wholesale Price.

[jespper-enablex]

Creating Interactive Digital Walkthroughs with Live Video Technology

In the contemporary digital landscape, live video services have become an indispensable tool for businesses, educators, entertainers, and developers alike. The evolution of technology has driven a surge in demand for real-time communication and interaction, fostering an environment where live video streaming has become a cornerstone of effective engagement.

This article explores the significance of live video services, particularly in the context of app development using Flutter, and delves into the various components that make these services crucial for successful live streaming.

The Rise of Live Video Streaming

Live video streaming has transformed the way content is consumed and delivered. Unlike pre-recorded videos, live streaming offers immediacy and interactivity, creating a sense of urgency and engagement that static content cannot match. This immediacy is particularly valuable in various scenarios, such as live events, online education, remote work, and real-time customer support.

Video Streaming in Flutter

Flutter, an open-source UI software development kit by Google, has gained immense popularity among developers for its ability to create natively compiled applications for mobile, web, and desktop from a single codebase. When it comes to video streaming in Flutter, the framework provides robust support through plugins and packages that simplify the integration of live video services. Utilizing Flutter for video streaming not only enhances the development process but also ensures a seamless and high-performance user experience.

The Importance of Real-Time Communication

Real-time communication is at the heart of live streaming, and it is this capability that distinguishes live video from other forms of media. The ability to interact in real-time is crucial for applications such as video call apps, video chat apps, and screen sharing functionalities.

Video Call App Flutter

Developing a video call app in Flutter allows developers to leverage the framework's strengths to create responsive and reliable communication tools. The integration of real-time communication features in Flutter apps is facilitated by a range of video call APIs and SDKs, which offer customizable and scalable solutions for various use cases.

Key Components of Live Video Services

To understand why live video services are crucial, it is essential to examine the key components that make up these services. These components include video call APIs, SDKs, and the overall infrastructure that supports real-time video streaming.

Video Call API

A video call API provides the necessary tools and protocols to implement video calling features in an application. APIs are designed to be developer-friendly, offering comprehensive documentation and support to streamline the integration process. When selecting a video call API, developers consider factors such as ease of use, compatibility with existing systems, and pricing.

Video Call SDK

A video call SDK (Software Development Kit) offers a more comprehensive solution by providing a set of tools, libraries, and documentation needed to build video calling features. SDKs are particularly valuable for developers looking to create robust and feature-rich video call applications without delving into the complexities of real-time communication protocols.

Video Call SDK Android

For Android developers, a video call SDK tailored for the platform simplifies the development process by providing native components and functionalities. This ensures optimal performance and integration with Android's ecosystem.

Video Call SDK Open Source

Open-source video call SDKs offer flexibility and transparency, allowing developers to customize and optimize their applications according to specific requirements. The open-source nature fosters community collaboration and continuous improvement, making these SDKs a popular choice among developers.

Benefits of Live Video Services

The integration of live video services into applications brings numerous benefits, enhancing both user experience and business outcomes.

Enhanced Engagement

Live video services foster real-time interaction, which significantly enhances user engagement. Whether it's a live stream of a product launch, a virtual classroom, or a customer support session, the ability to communicate and respond instantly creates a more dynamic and engaging experience.

Improved Collaboration

In the context of remote work and online collaboration, live video services play a pivotal role. Features like video chat and screen sharing in Flutter applications facilitate seamless communication and collaboration, bridging the gap between remote teams and enabling productive interactions.

Scalability and Flexibility

Modern video call APIs and SDKs are designed to be scalable, accommodating a growing number of users and varying levels of demand. This scalability ensures that applications can handle peak usage times without compromising performance. Additionally, the flexibility of these tools allows developers to tailor their solutions to meet specific needs, whether it's a small-scale video chat app or a large-scale streaming platform.

Cost-Effective Solutions

Utilizing video call APIs and SDKs can be a cost-effective approach to integrating live video services. Many providers offer tiered pricing models, allowing developers to choose plans that align with their budget and usage requirements. Open-source options further reduce costs while providing robust functionalities.

Use Cases of Live Video Services

The versatility of live video services makes them applicable across various industries and scenarios.

Education and E-Learning

In the realm of education, live video streaming has revolutionized the delivery of content. Virtual classrooms, live lectures, and interactive tutorials enable educators to reach a wider audience and provide personalized learning experiences. Flutter's capabilities make it an ideal choice for developing e-learning platforms with live video features.

Healthcare and Telemedicine

Telemedicine has seen significant growth, driven by the need for remote healthcare services. Live video consultations allow healthcare providers to diagnose and treat patients remotely, improving access to medical care. Flutter's cross-platform nature ensures that telemedicine apps can reach users on both mobile and web platforms.

Entertainment and Live Events

Live streaming is a cornerstone of the entertainment industry, enabling artists and creators to connect with their audience in real-time. From live concerts to virtual events, the integration of live video services ensures an immersive and interactive experience for viewers.

Customer Support and Engagement

Businesses leverage live video services to enhance customer support and engagement. Real-time video interactions enable support teams to assist customers more effectively, resolving issues promptly and building stronger customer relationships.

Conclusion

Live video services are crucial for successful live streaming due to their ability to provide real-time communication, enhance user engagement, and support various applications across different industries. With the rise of frameworks like Flutter, integrating live video features into applications has become more accessible and efficient.

By utilizing video call APIs, SDKs, and leveraging the strengths of Flutter, developers can create robust and scalable live streaming solutions that meet the evolving demands of today's digital landscape. Whether it's for education, healthcare, entertainment, or customer support, the importance of live video services cannot be overstated, making them an essential component of modern app development.

[bizmagnets]

Navigating the Future of Pharma: How BizMagnets Outperforms Tata 1mg ?

Ready to boost your Business with BizMagnets ?

Contact us for a demo, and let’s start your journey towards enhanced customer engagement, streamlined processes, and increased revenue.

Introduction:

In a time when digital platforms are changing how people access healthcare, pharmacies need to use new and innovative solutions to stay ahead in the market. 1mg has been a leader in providing digital pharmacy services, but a new platform called BizMagnets WhatsApp Business Suite is offering an interesting alternative, especially when it comes to providing personalized and efficient customer service

The Advantage of the WhatsApp Business API

WhatsApp has a huge number of users all around the world, which makes it a great way for pharmacies to communicate with and engage their customers in a more personal way. The BizMagnets suite, which uses the WhatsApp Business API, allows pharmacies to not only reach their customers but also really connect with them. This can provide services that go beyond what other online pharmacy platforms like 1mg currently offer.

How WhatsApp Business API Can Transform Your Pharmacy Business ?

1. Personalized Customer Journeys : The BizMagnets platform uses AI to provide each customer with a customized experience, which can help build customer loyalty and encourage repeat business, unlike the more generic interactions on platforms like 1mg.

2. Efficient Operations : Automating tasks like appointment booking, test scheduling, and order confirmations through WhatsApp can save time and reduce errors, making pharmacy operations more efficient.

3. Data-Driven Decisions : The advanced analytics capabilities of the BizMagnets platform allow pharmacies to gain valuable insights into customer behavior, which they can then use to make more informed business decisions and tailor their services more precisely

Provoking Thoughts

How could personalized WhatsApp messages transform your pharmacy’s customer service experience?

Imagine the efficiency gains from automating routine operations through WhatsApp. How would that change the day-to-day of your pharmacy?

With the insights provided by BizMagnets, what new services or products could you offer to meet the unique needs of your customers?

For a more in-depth analysis on how the WhatsApp Business API can empower pharmacies to outshine competitors like Tata 1mg through specific features like WhatsApp broadcast, drip campaigns, and Click to WhatsApp ads, let’s expand on each of these components, highlighting their benefits and potential impact on business growth

WhatsApp Broadcast: The Power of Personalized Messaging at Scale

WhatsApp Broadcast allows businesses to send messages to multiple customers at once, provided the customers have saved the business’s phone number in their contacts and have agreed to receive messages. This feature is pivotal for pharmacies in announcing new health products, vaccine availability, or seasonal health tips directly through WhatsApp, ensuring high visibility and engagement. Unlike 1mg’s approach, which may rely more on app notifications or emails, WhatsApp broadcasts feel more personal and are likely to be read by customers

Drip Campaigns: Nurturing Customer Relationships Over Time

Drip campaigns are automated sets of messages that are sent out based on specific timelines or user actions. For pharmacies leveraging BizMagnets, this means being able to automatically send a welcome series to new subscribers, educational content on managing chronic conditions, or reminders for prescription refills. This strategic communication keeps the pharmacy top of mind for customers and can encourage repeat purchases. Drip campaigns through WhatsApp can be more effective than traditional methods used by companies like Tata 1mg, due to the personal and immediate nature of messagingw

Click to WhatsApp Ads: Driving Conversations and Conversions

Click to WhatsApp ads are a powerful tool that integrates with Facebook and Instagram advertising platforms. When users click on an ad, they are directly taken to a WhatsApp conversation with the business. For pharmacies, this means being able to advertise specific products or health services and instantly engage with interested customers, providing personalized advice or facilitating orders directly through WhatsApp. This immediate engagement model can significantly outperform the more static online purchasing experience offered by platforms like 1mg, leading to higher conversion rates and customer satisfaction

The Competitive Edge

Implementing these features through the WhatsApp Business API offers a dynamic and interactive customer experience that stands in contrast to the more traditional, website-centric approach of competitors like 1mg

Here’s how:

Enhanced Personalization: WhatsApp allows for direct, one-on-one communication, making each customer feel valued and understood.

Higher Engagement Rates: Messages on WhatsApp have a higher open and read rate compared to emails and app notifications.

Path to Purchase: By reducing the steps needed to inquire or purchase, customers are more likely to complete transactions.

Empowering Businesses to Thrive in the Digital Age with BizMagnets

In today’s fast-paced, technology-driven business world, adapting and innovating is crucial. By partnering with BizMagnets and leveraging the power of the WhatsApp Business API, companies can gain a significant competitive edge. The BizMagnets.ai platform offers an AI-driven WhatsApp Business Suite that empowers businesses to provide personalized, efficient, and seamless customer communication.

This innovative solution allows companies to meet their customers where they are and deliver a superior customer experience It can gather essential information from leads based on predefined criteria, ensuring that sales teams focus their efforts on high-potential prospects.

Visit: https://bizmagnets.ai/navigating-the-future-of-pharma-how-bizmagnets-outperforms-1mg-with-bizmagnets/

Email: marketing@bizmagnets.ai

Contact Number: 7845079333

[techdriveplay]

What was Announced at WWDC 2024?

Apple’s Worldwide Developers Conference (WWDC) 2024 is in full swing, and the tech world is buzzing with excitement. This annual event is where Apple unveils its latest innovations across its ecosystem, from operating system updates to groundbreaking new products. Here’s a comprehensive look at the major announcements and features that have been revealed so far. Apple Vision Pro Expansion and…

[nuadox]

HIMSS24: Day 3 highlights

- By Danielle Siarri , Nuadox -

Here are our Day 3 highlights of the 2024 HIMSS Global Health Conference & Exhibition in Orlando (March 11-15).

Today, I was part of a discussion revolving around advancements in interoperability within the healthcare system, particularly within the U.S. Department of Veterans Affairs (VA).

Eliza Levy, representing the Lighthouse program, discussed the progress made in interoperability in the past five to eight years, highlighting initiatives like the Patient Health API and the Clinical Health API. These APIs enable veterans to access their health information securely and share it across various applications, improving their healthcare experience. There are over 20 applications already in production.

Furthermore, the discussion touched upon the importance of ethical frameworks for data access and use, as well as expanding the definition of interoperability to include end-user experience and business outcomes.

Questions from participants addressed topics such as ambient technology implementation and the future deployment of AI technology to reduce clinician burnout within the VA.

Additionally, the conversation focused on engaging diverse innovators and startups to further innovation in healthcare delivery.

Stay tuned for Day 4...

Read Also

HIMSS24: Day 1 highlights

HIMSS24: Day 2 highlights

HIMSS24: Day 4 highlights

[metricoid]

Transforming Mental Health: AI's Role in Wellness Apps

Discover how AI is reshaping mental health care, offering personalized, efficient support through wellness apps. From machine learning personalizing therapy to AI-enhancing mindfulness practices, we're uncovering how technology is not just an aid but a game-changer in mental health management. Join us as we navigate this exciting intersection of AI and psychology, revealing both its groundbreaking benefits and mindful considerations.

[bespokesoftwaredevelopment-blog]

Empowering Healthcare Solutions with Ficode's API Integration Services

Find solutions to your healthcare software development questions with Ficode's expert Third-Party API Integration services. Seamlessly connect diverse systems, enhance interoperability, and deliver solutions.

Our innovative approach ensures streamlined processes and improved patient care. Trust Ficode for transformative healthcare technology solutions.

[drnic1]

Healthcare's Digital Dilemma: Data Sharing or Data Hoarding?

Healthcare’s Digital Dilemma This week I am talking to Don Rucker, MD (@donrucker), Chief Strategy Officer, 1upHealth (@1up_health) who is working to solve the interoperability problem in healthcare Don shared his journey from being a medical student to a physician with a keen interest in data and computers. What he saw was healthcare’s inefficiency is often due to a lack of data, which led him…

[jcmarchi]

2023-24 Takeda Fellows: Advancing research at the intersection of AI and health

New Post has been published on https://thedigitalinsider.com/2023-24-takeda-fellows-advancing-research-at-the-intersection-of-ai-and-health/

2023-24 Takeda Fellows: Advancing research at the intersection of AI and health

The School of Engineering has selected 13 new Takeda Fellows for the 2023-24 academic year. With support from Takeda, the graduate students will conduct pathbreaking research ranging from remote health monitoring for virtual clinical trials to ingestible devices for at-home, long-term diagnostics.

Now in its fourth year, the MIT-Takeda Program, a collaboration between MIT’s School of Engineering and Takeda, fuels the development and application of artificial intelligence capabilities to benefit human health and drug development. Part of the Abdul Latif Jameel Clinic for Machine Learning in Health, the program coalesces disparate disciplines, merges theory and practical implementation, combines algorithm and hardware innovations, and creates multidimensional collaborations between academia and industry.

The 2023-24 Takeda Fellows are:

Adam Gierlach

Adam Gierlach is a PhD candidate in the Department of Electrical Engineering and Computer Science. Gierlach’s work combines innovative biotechnology with machine learning to create ingestible devices for advanced diagnostics and delivery of therapeutics. In his previous work, Gierlach developed a non-invasive, ingestible device for long-term gastric recordings in free-moving patients. With the support of a Takeda Fellowship, he will build on this pathbreaking work by developing smart, energy-efficient, ingestible devices powered by application-specific integrated circuits for at-home, long-term diagnostics. These revolutionary devices — capable of identifying, characterizing, and even correcting gastrointestinal diseases — represent the leading edge of biotechnology. Gierlach’s innovative contributions will help to advance fundamental research on the enteric nervous system and help develop a better understanding of gut-brain axis dysfunctions in Parkinson’s disease, autism spectrum disorder, and other prevalent disorders and conditions.

Vivek Gopalakrishnan

Vivek Gopalakrishnan is a PhD candidate in the Harvard-MIT Program in Health Sciences and Technology. Gopalakrishnan’s goal is to develop biomedical machine-learning methods to improve the study and treatment of human disease. Specifically, he employs computational modeling to advance new approaches for minimally invasive, image-guided neurosurgery, offering a safe alternative to open brain and spinal procedures. With the support of a Takeda Fellowship, Gopalakrishnan will develop real-time computer vision algorithms that deliver high-quality, 3D intraoperative image guidance by extracting and fusing information from multimodal neuroimaging data. These algorithms could allow surgeons to reconstruct 3D neurovasculature from X-ray angiography, thereby enhancing the precision of device deployment and enabling more accurate localization of healthy versus pathologic anatomy.

Hao He

Hao He is a PhD candidate in the Department of Electrical Engineering and Computer Science. His research interests lie at the intersection of generative AI, machine learning, and their applications in medicine and human health, with a particular emphasis on passive, continuous, remote health monitoring to support virtual clinical trials and health-care management. More specifically, He aims to develop trustworthy AI models that promote equitable access and deliver fair performance independent of race, gender, and age. In his past work, He has developed monitoring systems applied in clinical studies of Parkinson’s disease, Alzheimer’s disease, and epilepsy. Supported by a Takeda Fellowship, He will develop a novel technology for the passive monitoring of sleep stages (using radio signaling) that seeks to address existing gaps in performance across different demographic groups. His project will tackle the problem of imbalance in available datasets and account for intrinsic differences across subpopulations, using generative AI and multi-modality/multi-domain learning, with the goal of learning robust features that are invariant to different subpopulations. He’s work holds great promise for delivering advanced, equitable health-care services to all people and could significantly impact health care and AI.

Chengyi Long

Chengyi Long is a PhD candidate in the Department of Civil and Environmental Engineering. Long’s interdisciplinary research integrates the methodology of physics, mathematics, and computer science to investigate questions in ecology. Specifically, Long is developing a series of potentially groundbreaking techniques to explain and predict the temporal dynamics of ecological systems, including human microbiota, which are essential subjects in health and medical research. His current work, supported by a Takeda Fellowship, is focused on developing a conceptual, mathematical, and practical framework to understand the interplay between external perturbations and internal community dynamics in microbial systems, which may serve as a key step toward finding bio solutions to health management. A broader perspective of his research is to develop AI-assisted platforms to anticipate the changing behavior of microbial systems, which may help to differentiate between healthy and unhealthy hosts and design probiotics for the prevention and mitigation of pathogen infections. By creating novel methods to address these issues, Long’s research has the potential to offer powerful contributions to medicine and global health.

Omar Mohd

Omar Mohd is a PhD candidate in the Department of Electrical Engineering and Computer Science. Mohd’s research is focused on developing new technologies for the spatial profiling of microRNAs, with potentially important applications in cancer research. Through innovative combinations of micro-technologies and AI-enabled image analysis to measure the spatial variations of microRNAs within tissue samples, Mohd hopes to gain new insights into drug resistance in cancer. This work, supported by a Takeda Fellowship, falls within the emerging field of spatial transcriptomics, which seeks to understand cancer and other diseases by examining the relative locations of cells and their contents within tissues. The ultimate goal of Mohd’s current project is to find multidimensional patterns in tissues that may have prognostic value for cancer patients. One valuable component of his work is an open-source AI program developed with collaborators at Beth Israel Deaconess Medical Center and Harvard Medical School to auto-detect cancer epithelial cells from other cell types in a tissue sample and to correlate their abundance with the spatial variations of microRNAs. Through his research, Mohd is making innovative contributions at the interface of microsystem technology, AI-based image analysis, and cancer treatment, which could significantly impact medicine and human health.

Sanghyun Park

Sanghyun Park is a PhD candidate in the Department of Mechanical Engineering. Park specializes in the integration of AI and biomedical engineering to address complex challenges in human health. Drawing on his expertise in polymer physics, drug delivery, and rheology, his research focuses on the pioneering field of in-situ forming implants (ISFIs) for drug delivery. Supported by a Takeda Fellowship, Park is currently developing an injectable formulation designed for long-term drug delivery. The primary goal of his research is to unravel the compaction mechanism of drug particles in ISFI formulations through comprehensive modeling and in-vitro characterization studies utilizing advanced AI tools. He aims to gain a thorough understanding of this unique compaction mechanism and apply it to drug microcrystals to achieve properties optimal for long-term drug delivery. Beyond these fundamental studies, Park’s research also focuses on translating this knowledge into practical applications in a clinical setting through animal studies specifically aimed at extending drug release duration and improving mechanical properties. The innovative use of AI in developing advanced drug delivery systems, coupled with Park’s valuable insights into the compaction mechanism, could contribute to improving long-term drug delivery. This work has the potential to pave the way for effective management of chronic diseases, benefiting patients, clinicians, and the pharmaceutical industry.

Huaiyao Peng

Huaiyao Peng is a PhD candidate in the Department of Biological Engineering. Peng’s research interests are focused on engineered tissue, microfabrication platforms, cancer metastasis, and the tumor microenvironment. Specifically, she is advancing novel AI techniques for the development of pre-cancer organoid models of high-grade serous ovarian cancer (HGSOC), an especially lethal and difficult-to-treat cancer, with the goal of gaining new insights into progression and effective treatments. Peng’s project, supported by a Takeda Fellowship, will be one of the first to use cells from serous tubal intraepithelial carcinoma lesions found in the fallopian tubes of many HGSOC patients. By examining the cellular and molecular changes that occur in response to treatment with small molecule inhibitors, she hopes to identify potential biomarkers and promising therapeutic targets for HGSOC, including personalized treatment options for HGSOC patients, ultimately improving their clinical outcomes. Peng’s work has the potential to bring about important advances in cancer treatment and spur innovative new applications of AI in health care. 

Priyanka Raghavan

Priyanka Raghavan is a PhD candidate in the Department of Chemical Engineering. Raghavan’s research interests lie at the frontier of predictive chemistry, integrating computational and experimental approaches to build powerful new predictive tools for societally important applications, including drug discovery. Specifically, Raghavan is developing novel models to predict small-molecule substrate reactivity and compatibility in regimes where little data is available (the most realistic regimes). A Takeda Fellowship will enable Raghavan to push the boundaries of her research, making innovative use of low-data and multi-task machine learning approaches, synthetic chemistry, and robotic laboratory automation, with the goal of creating an autonomous, closed-loop system for the discovery of high-yielding organic small molecules in the context of underexplored reactions. Raghavan’s work aims to identify new, versatile reactions to broaden a chemist’s synthetic toolbox with novel scaffolds and substrates that could form the basis of essential drugs. Her work has the potential for far-reaching impacts in early-stage, small-molecule discovery and could help make the lengthy drug-discovery process significantly faster and cheaper.

Zhiye Song

Zhiye “Zoey” Song is a PhD candidate in the Department of Electrical Engineering and Computer Science. Song’s research integrates cutting-edge approaches in machine learning (ML) and hardware optimization to create next-generation, wearable medical devices. Specifically, Song is developing novel approaches for the energy-efficient implementation of ML computation in low-power medical devices, including a wearable ultrasound “patch” that captures and processes images for real-time decision-making capabilities. Her recent work, conducted in collaboration with clinicians, has centered on bladder volume monitoring; other potential applications include blood pressure monitoring, muscle diagnosis, and neuromodulation. With the support of a Takeda Fellowship, Song will build on that promising work and pursue key improvements to existing wearable device technologies, including developing low-compute and low-memory ML algorithms and low-power chips to enable ML on smart wearable devices. The technologies emerging from Song’s research could offer exciting new capabilities in health care, enabling powerful and cost-effective point-of-care diagnostics and expanding individual access to autonomous and continuous medical monitoring.

Peiqi Wang

Peiqi Wang is a PhD candidate in the Department of Electrical Engineering and Computer Science. Wang’s research aims to develop machine learning methods for learning and interpretation from medical images and associated clinical data to support clinical decision-making. He is developing a multimodal representation learning approach that aligns knowledge captured in large amounts of medical image and text data to transfer this knowledge to new tasks and applications. Supported by a Takeda Fellowship, Wang will advance this promising line of work to build robust tools that interpret images, learn from sparse human feedback, and reason like doctors, with potentially major benefits to important stakeholders in health care.

Oscar Wu

Haoyang “Oscar” Wu is a PhD candidate in the Department of Chemical Engineering. Wu’s research integrates quantum chemistry and deep learning methods to accelerate the process of small-molecule screening in the development of new drugs. By identifying and automating reliable methods for finding transition state geometries and calculating barrier heights for new reactions, Wu’s work could make it possible to conduct the high-throughput ab initio calculations of reaction rates needed to screen the reactivity of large numbers of active pharmaceutical ingredients (APIs). A Takeda Fellowship will support his current project to: (1) develop open-source software for high-throughput quantum chemistry calculations, focusing on the reactivity of drug-like molecules, and (2) develop deep learning models that can quantitatively predict the oxidative stability of APIs. The tools and insights resulting from Wu’s research could help to transform and accelerate the drug-discovery process, offering significant benefits to the pharmaceutical and medical fields and to patients.

Soojung Yang

Soojung Yang is a PhD candidate in the Department of Materials Science and Engineering. Yang’s research applies cutting-edge methods in geometric deep learning and generative modeling, along with atomistic simulations, to better understand and model protein dynamics. Specifically, Yang is developing novel tools in generative AI to explore protein conformational landscapes that offer greater speed and detail than physics-based simulations at a substantially lower cost. With the support of a Takeda Fellowship, she will build upon her successful work on the reverse transformation of coarse-grained proteins to the all-atom resolution, aiming to build machine-learning models that bridge multiple size scales of protein conformation diversity (all-atom, residue-level, and domain-level). Yang’s research holds the potential to provide a powerful and widely applicable new tool for researchers who seek to understand the complex protein functions at work in human diseases and to design drugs to treat and cure those diseases.

Yuzhe Yang

Yuzhe Yang is a PhD candidate in the Department of Electrical Engineering and Computer Science. Yang’s research interests lie at the intersection of machine learning and health care. In his past and current work, Yang has developed and applied innovative machine-learning models that address key challenges in disease diagnosis and tracking. His many notable achievements include the creation of one of the first machine learning-based solutions using nocturnal breathing signals to detect Parkinson’s disease (PD), estimate disease severity, and track PD progression. With the support of a Takeda Fellowship, Yang will expand this promising work to develop an AI-based diagnosis model for Alzheimer’s disease (AD) using sleep-breathing data that is significantly more reliable, flexible, and economical than current diagnostic tools. This passive, in-home, contactless monitoring system — resembling a simple home Wi-Fi router — will also enable remote disease assessment and continuous progression tracking. Yang’s groundbreaking work has the potential to advance the diagnosis and treatment of prevalent diseases like PD and AD, and it offers exciting possibilities for addressing many health challenges with reliable, affordable machine-learning tools. 

[getambee]

Canadian Wildfires: Impacts on the US AQI and Effective Measures to Mitigate Health Effects

Introduction

Wildfires are a natural phenomenon, but the frequency and intensity of these events have been increasing in recent years, driven by climate change and other factors. Canada, with its vast forests and wilderness areas, is no stranger to wildfires. These fires not only pose a significant threat to Canadian communities and ecosystems but can also have far-reaching consequences, including affecting air quality in neighboring countries like the United States. In this article, we will explore the impacts of Canadian wildfires on the US Air Quality Index (AQI), with a specific focus on New York City (NYC), and discuss effective measures to mitigate health effects. We will also provide information on how to access wildfire maps in Canada and utilize the Air Quality API to stay informed about air quality conditions.

The Canadian Wildfire Situation

Canada's vast landmass is home to numerous forests and wilderness areas, making it prone to wildfires, especially during the dry and hot summer months. The provinces of British Columbia, Alberta, and Ontario are particularly susceptible to wildfires. In recent years, climate change has exacerbated wildfire risks by creating conditions conducive to longer and more intense fire seasons.

Wildfires can release massive amounts of smoke and particulate matter into the atmosphere. The smoke can travel great distances, affecting air quality in regions far from the fire's origin. This phenomenon is not limited to Canadian borders; it often impacts air quality in the United States, particularly in states located to the south of Canada.

Impacts on the US AQI

The Air Quality Index (AQI) is a standardized measure used to communicate the quality of the air and the potential health risks associated with breathing it. When wildfires occur in Canada, the smoke they generate can be carried by prevailing winds into the United States, affecting AQI readings in various cities.

New York City (NYC) is one of the major urban areas on the eastern seaboard of the United States. While it may seem far removed from Canadian wildfires, it is not immune to their effects. The smoke from Canadian wildfires can reach NYC and lead to temporary spikes in the AQI. High AQI values can have serious health implications, especially for individuals with pre-existing respiratory conditions, the elderly, and young children.

In recent years, NYC has experienced instances where the AQI exceeded acceptable levels due to Canadian wildfires. This not only poses health risks but also necessitates public health advisories and action plans to protect vulnerable populations. It also highlights the interconnectedness of air quality across international borders and the importance of monitoring and responding to these events.

Accessing Wildfire Maps in Canada

One of the key steps in managing the impact of Canadian wildfires on US air quality is staying informed about the location and extent of wildfires in Canada. Fortunately, there are resources available to access up-to-date wildfire maps. When searching for such information, many individuals use the keyword "wildfire map Canada" to find the most relevant and current data.

Here are some resources and tips for accessing wildfire maps in Canada:

1. Government Websites: Both federal and provincial governments in Canada provide wildfire information on their official websites. Websites like Natural Resources Canada and provincial forestry agencies often have interactive maps that display active wildfires, their size, and containment efforts.

2. Mobile Apps: Many government agencies and organizations have developed mobile apps that provide real-time wildfire information. These apps often include features such as alerts, evacuation notices, and safety tips.

3. Wildfire Tracking Websites: Various websites like Ambee specialize in tracking wildfires across North America. These platforms aggregate data from multiple sources to provide comprehensive wildfire maps and information.

Utilizing the Air Quality API

To mitigate the health effects of poor air quality resulting from Canadian wildfires, it is crucial for individuals, especially those in affected regions like NYC, to stay informed about AQI readings. To cater to this need, organizations and individuals often rely on the Air Quality API to access real-time air quality data. When searching for AQI information for specific areas, the keyword "AQI NYC" is commonly used.

Here's how you can utilize the Air Quality API and make the most of it:

1. Mobile Apps: Many smartphone apps use the Air Quality API to provide users with real-time air quality information for their current location. Users can receive notifications when the AQI reaches certain thresholds, helping them take precautions.

2. Websites and Widgets: Several websites offer widgets that display AQI information for specific cities or regions. These can be embedded on personal websites or accessed directly for quick updates.

3. Alert Services: Some organizations and government agencies offer alert services that notify subscribers of significant changes in air quality, including spikes caused by wildfires. These alerts can help individuals take immediate action to protect their health.

Effective Measures to Mitigate Health Effects

When the AQI indicates poor air quality due to wildfire smoke, individuals should take steps to minimize exposure and protect their health. Here are some effective measures to consider:

1. Stay Informed: Keep track of AQI readings and follow local health advisories. Adjust your plans and activities accordingly, especially if you fall into a vulnerable category.

2. Limit Outdoor Activities: Minimize outdoor activities, especially strenuous exercise, when the AQI is high. If you must be outside, try to do so during periods of lower pollution levels.

3.Use Air Purifiers: Consider using air purifiers with HEPA filters in your home, especially in bedrooms, to reduce indoor air pollution. Make sure to properly maintain them for optimal performance.

4. Seal Your Home: Keep windows and doors closed to prevent smoke from entering your living space. Use weather stripping to seal any gaps.

5. Use N95 Masks: If you need to go outside during poor air quality conditions, wearing N95 masks can help filter out fine particulate matter. Ensure that the mask fits snugly for maximum effectiveness.

6. Stay Hydrated: Drink plenty of water to stay hydrated, as dry and smoky air can lead to dehydration.

7. Follow Medical Advice: If you have respiratory conditions like asthma or COPD, consult your healthcare provider for specific guidance and ensure you have an adequate supply of medications.

Conclusion

Canadian wildfires have far-reaching impacts, affecting not only Canada but also neighboring regions in the United States like New York City. Understanding the connection between these wildfires and the US AQI is crucial for public health and safety. By staying informed about wildfire locations through "wildfire map Canada" searches and monitoring AQI using "AQI NYC," individuals can take proactive measures to mitigate health effects. It is a collective responsibility to adapt to changing climate conditions, reduce the risk of wildfires, and protect our communities from the harmful consequences of poor air quality.

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[innonurse]

Infermedica launchs Intake API in order to improve patient care, minimize clinician burnout, and give intake data prior to care

- By InnoNurse Staff -

Infermedica, an AI-powered digital health platform that provides solutions for symptom analysis and patient triage, has expanded its API to incorporate Intake features. The new Intake API features are an expansion of the company's Medical Guidance Platform, which builds on its clinically verified Triage product.

The new API features are intended to increase clinician productivity while also personalizing the patient experience.

Read more at Infermedica/PRNewswire

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