#healthcare data visualization

[atozofsoftwareengineering]

25 Ways Healthcare Data is Revolutionizing the Healthcare Industry

An exhaustive list for healthcare and healthcareIT colleagues and friends. Happy Reading!

Healthcare data refers to the information collected from various sources in the healthcare system, including medical records, laboratory results, and insurance claims. This data can be used in numerous ways to advance healthcare and improve patient outcomes. From improving patient safety to developing personalized treatment plans, healthcare data is a valuable tool that can help healthcare…

[mitsde123]

What is Data Science? A Comprehensive Guide for Beginners

In today’s data-driven world, the term “Data Science” has become a buzzword across industries. Whether it’s in technology, healthcare, finance, or retail, data science is transforming how businesses operate, make decisions, and understand their customers. But what exactly is data science? And why is it so crucial in the modern world? This comprehensive guide is designed to help beginners understand the fundamentals of data science, its processes, tools, and its significance in various fields.

[dr-jeremia-j-pyuza-tips]

Letting others know is part of sharing. Please share anything good in the realm of education progress.

[dataonthecharts]

Maternity deaths in the United States vs the Healthcare spending

Source: World Bank Health Nutrition and Population Statistics

[p-p-c]

Unveiling a Healthcare Breakthrough: Global Healthcare Giant Saves $7.5 Million Annually with Intelligent & Unified Data Management

The pharmaceutical industry thrives on data, which plays a crucial role in every step, from clinical trials to regulatory compliance and drug development. However, amidst the vast amount of data generated daily, valuable insights often get lost in the maze of orphan files and dark data. Shockingly, research shows that 60–85% of unstructured data in shared storage setups remain in the dark.

Join us on their transformative journey, where they saved a staggering $7.5 million annually by reshaping their data landscape. Prepare to be inspired!

Click to read — https://bit.ly/3ISycK8

[emorphistechno]

Integrating Salesforce and Tableau could potentially revolutionize your business. By doing so, you can unlock a host of benefits while navigating through various challenges.

A business intelligence tool called Tableau aids in the visual representation of data through graphs and charts. Salesforce, on the other hand, is among the best customer relationship management programs available today. A corporation can gain a variety of advantages from the Salesforce Tableau integration in the most efficient way.  It has been determined that a corporation can only gain a sizable number of advantages through analyzing or reading data insights. Numerous advantages, including improved team communication, time savings, assistance with data analysis, and many others, are provided by integrating both of these tools. You must establish a connection with a Salesforce consulting firm if you want to fully benefit from the combination of Tableau and Salesforce.

[actu-real]

Healthcare efforts have soared, and so have healthcare costs. One of the major reasons behind rising healthcare costs is the lack of data-driven decision-making. There is a greater need for extensive data analytics, and to use the insights from it to make decisions that help reduce costs, improve quality and better treat at-risk patients.

Although data analytics is nothing new, healthcare organizations have the opportunity to take real world data analytics further and use it better to manage operations and reduce healthcare costs.

[tipdm]

ProtoTech Solutions can help you design, develop, and/or implement a medical data visualization tool. We have deep expertise in engineering interoperable healthcare software. We at ProtoTech can tackle challenges that Healthcare Organizations face in the process of visualizing data.

Know More: https://prototechsolutions.com/medical-visualization-enabling-a-revolution-in-healthcare/

[allthecanadianpolitics]

Source options for data about COVID-19 in Canada

COVID-19 Hazard Index

Communicates about COVID-19 risk, addresses misinformation

Publishes the Canadian COVID Forecast approximately every two weeks

The Hazard Index is calculated from 3 equally weighted categories: 1) Current infections and spread; 2) Healthcare system impact; 3) Mortality.

If you’d rather not check the website, Tara Moriarty (@MoriartyLab on twitter) regularly shares data visualizations outlining risk and what you can do to take precautions.

Canadian COVID-19 Wastewater Surveillance Dashboard

The wastewater dashboard shows the concentration of COVID-19 in wastewater samples from different sites.

Provides links to regional and local wastewater surveillance dashboards as well

Provincial and Territorial COVID-19 Data (update and reporting schedules vary)

British Columbia

Alberta

Saskatchewan

Manitoba

Ontario

Quebec

Newfoundland and Labrador

New Brunswick

Nova Scotia

Prince Edward Island

Yukon  *note: the data dashboard has been decommissioned

Northwest Territories wastewater monitoring

Nunavut *has not updated since April 2022

[girlgerard]

thinking about red and blue being an explicit and pretty unavoidable AIDS metaphor within killjoys really hits home how grounded and truthful all of gerard’s fantastical storylines are tbh.

within this universe of classic superhero neons, robots, and laser guns, not only is there commentary about commodification, chosen family, anti-capitalism (debatably imo), and even doctorow-esque data privacy, there’s also a deeply grounded illustration about the experiences of many queer people during the AIDS crisis. here you have red and blue, who are not only a lesbian couple but also sex workers who are discriminated against because of those intersections, navigating what is obviously meant to be read as the heathcare system. you have a storyline focusing on their dedication and love for one another, on the reality of being on the poverty line, of not being considered fully autonomous or deserving of rights based on the fact that they’re androids. you have a tragic decline of red slowly losing her hair, her blush, her skin cracking and her body shutting down as her battery dies. you have the incredibly pointed arc where blue, attempting to save red, gets denied a new battery, and has to attempt drastic and back-alley measures that ultimately fail. through this sci-fi overlay, gerard managed to write a deeply tragic and beautiful love story about two queer people and their relationships with each other, with sex work, with the healthcare system, with their economic status, and with AIDS in a comic that most people only know about because they heard nanana on the radio in 2013. and it’s only highlighted by how heavily 80s-inspired all of the killjoys visuals are.

obviously it can be read in many different ways, but thinking about gerard growing up near a major american city in the 1980s during the reagan administration and thinking about the depth that these two characters have even as side plots. idk. there isn’t exactly a point to this. i just really, really appreciate gerard as an artist. in every capacity

[zytes]

I know that the average person’s opinion of AI is in a very tumultuous spot right now - partly due to misinformation and misrepresentation of how AI systems actually function, and partly because of the genuine risk of abuse that comes with powerful new technologies being thrust into the public sector before we’ve had a chance to understand the effects; and I’m not necessarily talking about generative AI and data-scraping, although I think that conversation is also important to have right now. Additionally, the blanket term of “AI” is really very insufficient and only vaguely serves to ballpark a topic which includes many diverse areas of research - many of these developments are quite beneficial for human life, such as potentially designing new antibodies or determining where cancer cells originated within a patient that presents complications. When you hear about artificial intelligence, don’t let your mind instantly gravitate towards a specific application or interpretation of the tech - you’ll miss the most important and impactful developments.

Notably, NVIDIA is holding a keynote presentation from March 18-21st to talk about their recent developments in the field of AI - a 16 minute video summarizing the “everything-so-far” detailed in that keynote can be found here - or in the full 2 hour format here. It’s very, very jargon-y, but includes information spanning a wide range of topics: healthcare, human-like robotics, “digital-twin” simulations that mirror real-world physics and allow robots to virtually train to interact and navigate particular environments — these simulated environments are built on a system called the Omniverse, and can also be displayed to Apple Vision Pro, allowing designers to interact and navigate the virtual environments as though standing within them. Notably, they’ve also created a digital sim of our entire planet for the purpose of advanced weather forecasting. It almost feels like the plot of a science-fiction novel, and seems like a great way to get more data pertinent to the effects of global warming.

It was only a few years ago that NVIDIA pivoted from being a “GPU company” to putting a focus on developing AI-forward features and technology. A few very short years; showing accelerating rates of progress. This is whenever we began seeing things like DLSS and ray-tracing/path-tracing make their way onto NVIDIA GPUs; which all use AI-driven features in some form or another. DLSS, or Deep-Learning Super Sampling, is used to generate and interpolate between frames in a game to boost framerate, performance, visual detail, etc - basically, your system only has to actually render a handful of frames and AI generates everything between those traditionally-rendered frames, freeing up resources in your system. Many game developers are making use of DLSS to essentially bypass optimization to an increasing degree; see Remnant II as a great example of this - runs beautifully on a range of machines with DLSS on, but it runs like shit on even the beefiest machines with DLSS off; though there are some wonky cloth physics, clipping issues, and objects or textures “ghosting” whenever you’re not in-motion; all seem to be a side effect of AI-generation as the effect is visible in other games which make use of DLSS or the AMD-equivalent, FSR.

Now, NVIDIA wants to redefine what the average data center consists of internally, showing how Blackwell GPUs can be combined into racks that process information at exascale speeds — which is very, very fucking fast — speeds like that have only ever actually been achieved on some 4 or 5 machines on the planet, and I think they’ve all been quantum-based machines until now; not totally certain. The first exascale computer came into existence in 2022, called Frontier, it was deemed the fastest supercomputer in existence in June 2023 - operating at some 1.19 exaFLOPS. Notably, this computer is around 7,300 sq ft in size; reminding me of the space-race era supercomputers which were entire rooms. NVIDIA’s Blackwell DGX SuperPOD consists of around 576 GPUs and operates at 11.5 exaFLOPS, and is about the size of standard row of server racks - much smaller than an entire room, but still quite large. NVIDIA is also working with AWS to produce Project Ceiba, another supercomputer consisting of some 20,000GPUs, promising 400 exaFLOPS of AI-driven computation - it doesn’t exist yet.

To make my point, things are probably only going to get weirder from here. It may feel somewhat like living in the midst of the Industrial Revolution, only with fewer years in between each new step. Advances in generative-AI are only a very, very small part of that — and many people have already begun to bury their heads in the sand as a response to this emerging technology - citing the death of authenticity and skill among artists who choose to engage with new and emerging means of creation. Interestingly, the Industrial Revolution is what gave birth to modernism, and modern art, as well as photography, and many of the concerns around the quality of art in this coming age-of-AI and in the post-industrial 1800s largely consist of the same talking points — history is a fucking circle, etc — but historians largely agree that the outcome of the Industrial Revolution was remarkably positive for art and culture; even though it took 100 years and a world war for the changes to really become really accepted among the artists of that era. The Industrial Revolution allowed art to become detached from the aristocratic class and indirectly made art accessible for people who weren’t filthy rich or affluent - new technologies and industrialization widened the horizons for new artistic movements and cultural exchanges to occur. It also allowed capitalist exploitation to ingratiate itself into the western model of society and paved the way for destructive levels of globalization, so: win some, lose some.

It isn’t a stretch to think that AI is going to touch upon nearly every existing industry and change it in some significant way, and the events that are happening right now are the basis of those sweeping changes, and it’s all clearly moving very fast - the next level of individual creative freedom is probably only a few years away. I tend to like the idea that it may soon be possible for an individual or small team to create compelling artistic works and experiences without being at the mercy of an idiot investor or a studio or a clump of illiterate shareholders who have no real interest in the development of compelling and engaging art outside of the perceived financial value that it has once it exists.

If you’re of voting age and not paying very much attention to the climate of technology, I really recommend you start keeping an eye on the news for how these advancements are altering existing industries and systems. It’s probably going to affect everyone, and we have the ability to remain uniquely informed about the world through our existing connection with technology; something the last Industrial Revolution did not have the benefit of. If anything, you should be worried about KOSA, a proposed bill you may have heard about which would limit what you can access on the internet under the guise of making the internet more “kid-friendly and safe”, but will more than likely be used to limit what information can be accessed to only pre-approved sources - limiting access to resources for LGBTQ+ and trans youth. It will be hard to stay reliably informed in a world where any system of authority or government gets to spoon-feed you their version of world events.

[tech-insides]

What are the skills needed for a data scientist job?

It’s one of those careers that’s been getting a lot of buzz lately, and for good reason. But what exactly do you need to become a data scientist? Let’s break it down.

Technical Skills

First off, let's talk about the technical skills. These are the nuts and bolts of what you'll be doing every day.

Programming Skills: At the top of the list is programming. You’ll need to be proficient in languages like Python and R. These are the go-to tools for data manipulation, analysis, and visualization. If you’re comfortable writing scripts and solving problems with code, you’re on the right track.

Statistical Knowledge: Next up, you’ve got to have a solid grasp of statistics. This isn’t just about knowing the theory; it’s about applying statistical techniques to real-world data. You’ll need to understand concepts like regression, hypothesis testing, and probability.

Machine Learning: Machine learning is another biggie. You should know how to build and deploy machine learning models. This includes everything from simple linear regressions to complex neural networks. Familiarity with libraries like scikit-learn, TensorFlow, and PyTorch will be a huge plus.

Data Wrangling: Data isn’t always clean and tidy when you get it. Often, it’s messy and requires a lot of preprocessing. Skills in data wrangling, which means cleaning and organizing data, are essential. Tools like Pandas in Python can help a lot here.

Data Visualization: Being able to visualize data is key. It’s not enough to just analyze data; you need to present it in a way that makes sense to others. Tools like Matplotlib, Seaborn, and Tableau can help you create clear and compelling visuals.

Analytical Skills

Now, let’s talk about the analytical skills. These are just as important as the technical skills, if not more so.

Problem-Solving: At its core, data science is about solving problems. You need to be curious and have a knack for figuring out why something isn’t working and how to fix it. This means thinking critically and logically.

Domain Knowledge: Understanding the industry you’re working in is crucial. Whether it’s healthcare, finance, marketing, or any other field, knowing the specifics of the industry will help you make better decisions and provide more valuable insights.

Communication Skills: You might be working with complex data, but if you can’t explain your findings to others, it’s all for nothing. Being able to communicate clearly and effectively with both technical and non-technical stakeholders is a must.

Soft Skills

Don’t underestimate the importance of soft skills. These might not be as obvious, but they’re just as critical.

Collaboration: Data scientists often work in teams, so being able to collaborate with others is essential. This means being open to feedback, sharing your ideas, and working well with colleagues from different backgrounds.

Time Management: You’ll likely be juggling multiple projects at once, so good time management skills are crucial. Knowing how to prioritize tasks and manage your time effectively can make a big difference.

Adaptability: The field of data science is always evolving. New tools, techniques, and technologies are constantly emerging. Being adaptable and willing to learn new things is key to staying current and relevant in the field.

Conclusion

So, there you have it. Becoming a data scientist requires a mix of technical prowess, analytical thinking, and soft skills. It’s a challenging but incredibly rewarding career path. If you’re passionate about data and love solving problems, it might just be the perfect fit for you.

Good luck to all of you aspiring data scientists out there!

[satyaranjan7605]

GIS In Our Daily Lives

The involvement of Geographic Information Systems (GIS) in our daily lives is pervasive, influencing and enhancing various aspects across different sectors. The integration of GIS into everyday activities has become integral for decision-making, planning, and optimizing resources. GIS helps city planners and transportation experts to provide them with information like maps, satellite pictures, population statistics, and infrastructure data. GIS helps them make better decisions when designing cities and transportation systems that are sustainable and good for the environment.

The following points elucidate the notable involvement of GIS in our daily lives:

Navigation and Location Services: GIS provides monitoring functions through the visual display of spatial data and precise geographical positioning of monitored vehicles, whereas GPS provides accurate, clear, and precise information on the position and navigation of a monitored or tracked vehicle in real-time and at the exact location.GIS is at the core of navigation applications and location-based services on smartphones. It enables accurate mapping, real-time navigation, and geolocation services, assisting individuals in finding locations, planning routes, and navigating unfamiliar areas.

E-Commerce and Delivery Services: GIS software is a powerful tool for supply chain network planning. It helps determine the optimal location for distribution centers, warehouses, or other supply facilities. GIS is utilized in logistics and delivery services for optimizing routes, tracking shipments, and ensuring timely deliveries. E-commerce platforms leverage GIS to enhance the efficiency of their supply chain and last-mile delivery processes.

Weather Forecasting and Disaster Management: Many states are using GIS dashboard to monitor the rainfall across the state, on a real-time basis, from the data shared by rain sensors installed at various locationsGIS plays a crucial role in weather forecasting and disaster management. It assists meteorologists in analyzing spatial data, predicting weather patterns, and facilitating timely responses to natural disasters by mapping affected areas and coordinating emergency services.

Healthcare Planning and Disease Monitoring: Geographic Information Systems enable the visualization and monitoring of infectious diseases. Additionally GIS records and displays the necessary information that health care needs of the community as well as the available resources and materials. GIS supports public health initiatives by mapping the spread of diseases, analyzing healthcare resource distribution, and assisting in the planning of vaccination campaigns. It aids in identifying high-risk areas and optimizing healthcare service delivery.

Social Media and Geo-tagging: GIS also helps in geotagging and other location related information in posts, it’s tools can map and visualize the spatial distribution of social media activity. This analysis can reveal trends, hotspots, and patterns in user engagement across different geographic areas. Many social media platforms incorporate GIS for geo-tagging, allowing users to share their location and experiences. This feature enhances social connectivity and facilitates the sharing of location-specific information.

Smart City Initiatives: The Geographic Information System (GIS) offers advanced and user-friendly capabilities for Smart City projects and allows to capture, store and manipulate, analyze and visualize spatially referenced data. It is used for spatial analysis and modeling. It is the cornerstone of smart city planning, enabling the integration of data for efficient urban management. It supports initiatives related to traffic management, waste disposal, energy consumption, and overall infrastructure development.

Education and Research: GIS is increasingly utilized in education and research for visualizing and analyzing spatial data. It enables students and researchers to explore geographic relationships, conduct field studies, and enhance their understanding of various subjects.

Agricultural Management and Precision Farming: Farmers leverage GIS to optimize agricultural practices by analyzing soil conditions, crop health, and weather patterns. Precision farming techniques, facilitated by GIS, contribute to increased crop yields and sustainable farming practices.

Real Estate and Property Management: In the real estate sector, GIS aids in property mapping, land valuation, and site selection. It provides real estate professionals with valuable insights into spatial relationships, market trends, and optimal development opportunities.

Tourism and Recreation: GIS enhances the tourism industry by providing interactive maps, route planning, and location-based information. It assists tourists in exploring destinations, finding attractions, and navigating efficiently.

The broad and varied involvement of GIS in our daily lives underscores its significance as a technology that not only facilitates geographic data analysis but also contributes to the efficiency, safety, and interconnectedness of modern society. As GIS applications continue to evolve, their impact on daily activities is expected to further expand and refine.

[entitycradle]

Future Anime Girl Gestalt

As a breakthrough in silicon nanostructure materials makes photonics and near-eye displays cheap, smart glasses become the new ubiquitous computers, replacing smartphones. The always-on display provides unique opportunities for advertisers, as does new machine learning-assisted ad targeting. In the new omnipresent augmented reality, ads become personalized, three-dimensional, interactive displays, emerging from blank rectangles in subway stations. You see your facebook friends conversing animatedly, drinking budweiser.

As smart glasses become increasingly necessary for modern life, brands are able to invade further into perceived reality. Cars shine luxuriously. The name and price of your coworker's smartwatch floats above it. Of course many modern advertisements no longer directly sell a product or service, but rather create and maintain brand identities. Large corporations advertise on everyday objects--the plate at your favorite restaurant reveals the name of a software company as you finish your food. Your brother's anger turns him super saiyan, reminding you of the new episodes. A poor neighborhood turns into an alien-inspired techno-organic nightmare.

Many companies use characters to perpetuate their brand. These characters can be personalized--the insurance company mascot that shows up on your car dashboard during a harrowing rush hour is your favorite color, features large, expressive eyes, and is covered in shaggy fur.

Of course, machine learning algorithms can be unpredictable. And ad agencies could not anticipate the omnivalent memetic power of...

...anime girls.

The algorithm customizes your pepsi soda into a fizzy anime slime girl. They customize the call to your healthcare provider to raise the pitch of the representative's voice and translate the audio to Japanese (your glasses display English subtitles). The missiles you see striking a city in Iran are ridden by pale, northrop grumman-labeled anime maids.

As more human agency is ceded to enormous, power-chugging processing centers, the connections between everyday occurrences and brand presence become more abstract. Every character on a show you're not paying attention to, every old shoe you own, every person you interact with, every grain of sand on the beach, every floater in your eye, is an anime girl.

As humans do, they adapt. Generation Glass becomes accustomed to experiencing two entirely foreign sets of sense-data: one, their local, mundane world, of humming processors and concrete and scraggly trees. The other, the networked world, where your entire visual field is painted in overlapping anime girls of various sizes and your auditory vestibular nerve is drowned in high-pitched giggling. Each girl represents some object--pomegranate, sunset, friends, love, death.

As global civilization gently deflates under the pressure of climate change post-2100, so does the capacity to manufacture complex electronics. Within the space of a generation, billions of people are reduced to creating facile, vapid illustrations of the moving, living anime girls they once knew as bigotry and tarmac. Pictures of anime girls are used to label street signs, mathematical concepts, genders, religious texts. Ironically, anime girls become more incorporated into the real world than they ever were in the Glass period, because they adorn real surfaces. A post-traumatic behavior develops, in which a person destroys objects bearing anime girl images in an attempt to, according to one individual, "let them out," or otherwise restore networked consensus reality.

Thousands of years pass. Peregrine sophists of the Fifth Yyrzoc clan uncover an underground concrete structure. In it are glyphs of a single, big-eyed, pale, skinny, large-breasted woman with bright blue hair, surrounded by female figures in blood-red uniforms who are collapsed on the ground. The sophists are able to decode this message and avoid what we would recognize as a nuclear waste storage facility. They theorize that the figures are ancient feminine gods of radiation and death. Several etchings and illustrations are published by a notable scriptorium. Years later they are largely forgotten.

[p-p-c]

Cloud Tiering: A Solution for Pharma’s Storage Divestiture Dilemma

The pharmaceutical industry is experiencing an incredible surge in data generation! Research, clinical trials, and patient info are driving this growth. With massive potential for innovation and better healthcare outcomes, there are also major challenges in managing and storing this data. But guess what? Storage divestitures are here to save the day! By offloading storage assets strategically and adopting cloud storage solutions, pharmaceutical organizations can cut costs, boost efficiency, and unlock new avenues for innovation. Curious about storage divestitures? Let's dive in and explore what they really are and how can they help boost your profits!

Click to read - https://bit.ly/45ucgPe

[wumblr]

the slope of the death rate in gaza seems to be getting less steep, and the estimate of missing people (7000) has not increased in weeks

i don't have data as granular as this looks, i've been taking totals that are cited to have come from the health ministry, and dividing the difference from the last published total by the number of intervening days. (october has daily numbers given at a press release oct 31, which i think i got directly from the health ministry's website, in a rare instance where the page would load for me)

so, the salient visualization here is several angles, over a few weeks, in between each update from the health ministry. the most recent few updates are not as much higher as past updates have been, and so far this seems to be a consistent trend over the course of the conflict. the majority of violence seems to be biased toward the beginning

this could be for a number of reasons -- there are few healthcare sites left to report deaths, i may have prematurely counted some -- or the pace of violence is genuinely slowing (about 100/day now compared to 400/day in november)

(we have not lost another 0.01% of US population to covid since november. that IS incontrovertibly slower)