#healthcare big data industry

[techdriveplay]

Why Quantum Computing Will Change the Tech Landscape

The technology industry has seen significant advancements over the past few decades, but nothing quite as transformative as quantum computing promises to be. Why Quantum Computing Will Change the Tech Landscape is not just a matter of speculation; it’s grounded in the science of how we compute and the immense potential of quantum mechanics to revolutionise various sectors. As traditional…

[ai-innova7ions]

Video Automatically Generated by Faceless.Video:

Revolutionize Your Data Security with AI Models!

Small language models are revolutionizing the tech landscape by providing a more efficient alternative to larger counterparts. Their ability to operate on modest hardware means they can run locally, making them perfect for industries like healthcare and finance where data privacy is crucial.

These models enable fast and secure processing of sensitive information, transforming how businesses manage data. By addressing privacy concerns without compromising performance, small language models are paving the way for innovative solutions in various sectors. Discover how these advancements impact our world today!

#SmallLanguageModels

#DataPrivacy

[techtoio]

Emerging Tech Trends in the Internet of Things (IoT)

Introduction

The Internet of Things (IoT) is transforming our world by connecting devices and enabling smarter, more efficient interactions. In everything from smart homes to industrial automation, the IoT is leading a revolution in our living and working environments. In this article, TechtoIO explores the emerging tech trends in IoT, highlighting the innovations and advancements that are shaping the future. Read to continue link

[123567-9qaaq9]

Big Data Healthcare Market | BIS Research

In today's world, data is king. Industries across the board are leveraging the power of data to drive decision-making, streamline processes, and innovate in ways never before imagined. Nowhere is this more evident than in the healthcare sector, where the utilization of big data is revolutionizing patient care, research, and operational efficiency. The Big Data Healthcare Market Report offers a comprehensive glimpse into this burgeoning field, exploring its current landscape, trends, challenges, and future prospects.

The global big data in healthcare market amounted to $11.45 billion in 2016 and is expected to witness a double-digit growth throughout the forecast period of 2017-2025.

Understanding the Big Data Healthcare Market

The Big Data Healthcare Market encompasses a wide array of technologies, solutions, and services aimed at harnessing the immense volume, variety, and velocity of healthcare data. This includes electronic health records (EHRs), medical imaging, wearable devices, genomics, and more. The market is driven by the increasing digitization of healthcare data, coupled with advancements in data analytics, machine learning, and artificial intelligence (AI).

Key Trends Shaping the Landscape

Several key trends are shaping the Big Data Healthcare Market:

Predictive Analytics: Healthcare providers are increasingly using predictive analytics to forecast patient outcomes, identify at-risk populations, and personalize treatment plans. By analyzing historical data and real-time inputs, predictive models can help improve clinical decision-making and preventive care.

Precision Medicine: Big data analytics is instrumental in the advancement of precision medicine, which tailors medical treatment to individual characteristics such as genetics, lifestyle, and environment. By analyzing large datasets, researchers can identify biomarkers, understand disease pathways, and develop targeted therapies.

Real-Time Monitoring: Wearable devices and remote monitoring technologies generate vast amounts of real-time health data. Big data analytics enable healthcare professionals to monitor patients remotely, detect anomalies, and intervene proactively, thereby improving patient outcomes and reducing healthcare costs.

Population Health Management: Big data analytics play a crucial role in population health management, enabling healthcare organizations to identify patterns, trends, and disparities within populations. By segmenting populations based on risk factors and healthcare needs, providers can implement targeted interventions to improve population health and reduce disparities.

Challenges and Opportunities

While the potential of big data in healthcare is vast, it is not without its challenges. Data privacy and security concerns, interoperability issues, and the complexities of data integration are among the primary hurdles facing the industry. Moreover, the sheer volume and variety of healthcare data present challenges in terms of storage, processing, and analysis.

However, these challenges also present opportunities for innovation and growth. As technology continues to advance, solutions for data interoperability, privacy, and security are emerging. Furthermore, the integration of big data analytics with emerging technologies such as blockchain and edge computing holds promise for overcoming existing challenges and unlocking new possibilities in healthcare.

Grab a look at the free sample @ Big Data Healthcare Market Report 

Future Outlook

The future of the Big Data Healthcare Market is bright, with continued growth expected in the coming years. The increasing adoption of electronic health records, the proliferation of connected devices, and ongoing advancements in data analytics and AI will drive market expansion. Moreover, the COVID-19 pandemic has underscored the importance of data-driven decision-making in healthcare, further accelerating the adoption of big data technologies.

In conclusion, the Big Data Healthcare Market represents a transformative force in the healthcare industry, offering unprecedented opportunities to improve patient outcomes, enhance operational efficiency, and drive innovation. As stakeholders continue to invest in data-driven technologies and solutions, the potential for positive impact on global health outcomes is immense.

[drnic1]

Data Driven Conversations

This week I am talking to Sanjula Jain, PhD (@sanjula_jain), SVP Market Strategy & Chief Research Officer at Trilliant Health (@TrilliantHealth), a company focused on healthcare industry expertise, market research, and predictive analytics to create evidence-based direction for Healthcare. Sanjula has like many of my guests an interesting background and origin story but in her case set her on a…

[tntra]

Explore the transformative potential of big data analytics in healthcare from a new economy perspective. This insightful blog delves into the benefits and applications of big data analytics in the healthcare industry, including improved patient outcomes, personalized medicine, predictive analytics, and operational efficiency. Discover how harnessing the power of big data can drive innovation, enhance decision-making, and optimize healthcare delivery. Stay ahead of the curve and unlock the full potential of big data analytics in revolutionizing healthcare.

[d0nutzgg]

Scraper is Done but Needs Improvement

So my scraper is "done" but I realized that ffmpeg does not convert the files from mp4 to mp3 like I need for my dataset, it is a great start but now I have to delete 500 files off my computer :D

[metamatar]

$200k seems like quite a reasonable cost for a small sterile lab. It's not a plan to make it at home, it's a plan to make it in your town. As of now, there are so few insulin plants that the economies of scale aren't optimal for distribution (but they are for profits!)

did you miss the part that it was speculative? that it has never been demonstrated? also no, the economies of scale are fine for distribution cold chain distribution it is a solved problem. people aren't struggling to get insulin bc it can't be delivered, they're struggling bc its expensive.

im not sure you understand what economies of scale means, it means when you try to do things at larger scale – you are generally able to deploy productive technologies and innovations in organisation (specialisation) which make things easier to produce (less labour and capital input) on average. things become cheaper to produce. it is cheaper to weave cloth at a factory than in a loom you install in your backyard. that's why open insulin can only hypothetically get a vial down to the price of for profit insulin in the uk. big pharma is able to profit from insulin at 7 dollars a vial, ie it's even cheaper to produce. this is like, adam smith pin example.

the existence of a big factory or doing things at scale doesn't create destructive megaprofits... this is such a bizarre worldview of the world. you have to make a very sophisticated argument to prove this, which imo is immediately debunked by the reality of worker organised cooperatives in factories or even state run industrial production. profit tends to be a function of factors like labour relations + market dynamics like supply, demand and competition. us healthcare sucks bc your workers don't have rights, private insurance colludes with hospitals and competitors and the govt doesn't regulate pharma companies who are providing an inelastic good (medicine.)

also addressing this bc some people are mad at me but the only part of my argument that cites a piece hosted on RAND corp is the extremely high price of US insulin compared to every other country in the world. its like 30x. i don't think that is a fact that's a capitalist conspiracy, the data can be confirmed with other sources too, it just illustrates how dysfunctional US healthcare is. like, when your enemies agree...

[brandyschillace]

As it’s non-binary awareness week, I thought I’d share my bio—an attempt to say where I’ve been and what I’m about. And why I am she/her but mean that in a very plural sort of way.

I grew up in an underground house, next to a graveyard, in abandoned coal lands… with a pet raccoon. Oddly, this tends not to surprise people as much as I think it will. My rural community skirted the poverty line, a place of failed industry and orange rivers, poor health, and poorer access to healthcare. As a result, I spent my childhood reading a lot about disease and going to a lot of funerals. I ended up with a Ph.D. and a career in science history, which is probably a likely thing to happen when you spend your early years in a cemetery.

I’ve worked in an English Department, a History Department, and for a Medical Anthropology journal. I spent five years as a research associate in a medical museum among amputation saws, surgery kits, and smallpox vaccines—and now, in addition to being an author, I’m Editor-in-Chief for BMJ’s Medical Humanities Journal. I tend to fall outside the borders and binaries on every side. It’s not that I eschew being a ‘woman’ but that the box isn’t big enough to contain the selves that are me.

I always liked the line by Walt Whitman: I contain multitudes. Each of us are completely unique sets of data and DNA, blood and bones, bits and pieces of ancient stardust (and some microplastics). We don’t just have fingerprints. We are fingerprints — completely unique phenomenon in the universe, never before and never to be again. I am a truck, a train, a bulldog in a wind-tunnel; I’m also autistic. I live in the middle spaces where the contradictions are, containing bits of astral matter, aspects of both genders and possibly some dragons and vampires. I do history the way most people climb mountains–I get my hands dirty–I end up in catacombs, archives, basements. As you can imagine, this sort of thing doesn’t fit in a box very well. Then again, life is more interesting at the intersections.

[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!

[saetoru]

I just read your post about Ai and can I just share that I work in archeology and I'm absolutely terrified of the way AI is becoming normalized within research. The University I work for recently granted our department a large budget for this research project, and instead of hiring new people, or taking even taking in undergrad students as assistant researchers, my superiors have been using ChatGPT. It's absolutely insane to me that it is being recommended for us to use it to create surveys and organize our collected data. we are even being told to use it if we're having trouble writing the summary reports that help us continue getting funding.

I use it almost everyday, and it is not 100% accurate. Its actually wrong a lot of the time when you're using it to do more advanced math so it's very worrisome that it's being used for quantitative research. it is so easy for things to be wrong and no one to even notice.

YES ITS SO SCARY !!! im in healthcare management and the company i’m working with is a supplier for hospitals and the way they use chat gpt to compare pricing and break down data and even just write emails for summaries is so scary because the calculations aren’t always correct and they admit that !! and they still use it !! means for breaking down data aren’t always the most effective. and it’s especially scary bc my friend who is a pharm tech has been consistently complaining that more and more drugs have become hard to order in larger quantities and they are having loads of shortages. they’ve had to limit how much they can give at a time significantly in a few pharmacies in my area and it’s like. if you chat gpt things like calculating when it comes to supplying things for the healthcare industry, you heavily risk accidentally miscalculating how you split things up or wtv the case may be and already scarce items will be even more scarce. it’s just a very very nauseating thing to hear — and young ppl especially !! the company i’m working with has also cut back so many interning spots with data analytics bc they rely on ai to do it !! there are so many young individuals that are slowly being robbed of experience they desperately need to build their careers and the economy isn’t exactly helping with the case either, and :,) it’s just. a rly rly big area for concern bc there seems to be no regulation whatsoever and i can’t wrap my head around it.

and besides the professional aspect, there’s also the social aspect you have to consider. ai generated images are becoming more and more accurate and we’re living in a time where we can start to make anyone’s voice and faces be generated to say / look however we want. there are so many dangers to that i don’t even think i need to go into but from every standpoint all ai screams to me is a way to make life more and more miserable instead of efficient :,)

[grits-galraisedinthesouth]

CDC Appointment

Dave Weldon, MD

Former Florida Representative Dave Weldon, MD, was chosen by President-elect Donald Trump to lead the Centers for Disease Control and Prevention (CDC), replacing Mandy K. Cohen.

“In addition to being a Medical Doctor for 40 years, and an Army Veteran, Dave has been a respected conservative leader on fiscal and social issues, and served on the Labor/HHS Appropriations Subcommittee, working for Accountability on HHS and CDC Policy and Budgeting,” Trump said in the Friday evening announcement. 

“Dave also served in a leading role in Government Oversight and Reform Committee Hearings, addressing issues within HHS and CDC. Dave has successfully worked with the CDC to enact a ban on patents for human embryos,” Trump said.

According to Trump, Dr. Weldon will be instrumental in “Making America Healthy Again,” focusing on fixing the previous administration’s “past errors.”

“Americans have lost trust in the CDC and in our Federal Health Authorities, who have engaged in censorship, data manipulation, and misinformation,” he said. 

“Given the current Chronic Health Crisis in our Country, the CDC must step up and correct past errors to focus on the Prevention of Disease. The current Health of Americans is critical, and CDC will play a big role in helping to ensure Americans have the tools and resources they need to understand the underlying causes of diseases, and the solutions to cure these diseases,” Trump added.

The president-elect also noted that Dr. Weldon “understands American Family Values.”

“As a father of two and a husband of 45 years, Dave understands American Family Values, and views Health as one of utmost importance,” he said. “Dave will prioritize Transparency, Competence, and High Standards at CDC. Dave will proudly restore the CDC to its true purpose, and will work to end the Chronic Disease Epidemic, and Make America Healthy Again!”

From Dave Weldon for Senate

Dave Weldon and Nancy, his wife of 32 years, have two children, aged 25 and 14. Dr. Weldon was born on Long Island, New York to Anna and Dave Weldon, Sr., a combat-decorated WWII veteran.

After graduating Phi Beta Kappa from SUNY Stony Brook, he earned his MD degree at SUNY Buffalo School of Medicine in 1981 and was inducted into the Alpha Omega Alpha National Medical Honor Society upon completing a three-year accelerated medical degree.

Dr. Weldon went to medical school on an Army Health Professions Scholarship and did his internship and residency in internal medicine at Letterman Army Medical Center in San Francisco. He served a total of six years on active duty and eight years in the Army Reserves, achieving the rank of Major.

In 1987, Dr. Weldon went into private practice in Florida with Melbourne Internal Medicine Associates (MIMA), at the time a 20-physician member group practice.

In 1994, he ran successfully for Congress, becoming part of the first Republican majority in the U.S. House in 40 years. He served seven terms in Congress, on committees and caucuses including the Science Committee, the Education and Workforce Committee, Banking and Financial Services, Government Reform and Oversight, and the Appropriations Committee. He was also a member of the conservative Republican Study Committee and served on the Speaker’s Task Force on Healthcare Reform in his freshman term.

Florida’s District 15 is known as “The Space Coast,” which, during Dr. Weldon’s service in Congress, encompassed Kennedy Space Center and was home to the nation’s Space Shuttle, Patrick Air Force Base and Cape Canaveral Air Station. He was one of the founding members of the Aerospace Caucus, which worked closely with the Aerospace Industries Association to promote job growth and support our nation’s aerospace industrial base and national defense.

As a physician, Dr. Weldon became involved with many health care policy issues, including efforts to ban human cloning and vaccine safety. He helped lead the effort to remove toxic mercury containing preservatives from childhood vaccines. For his health care work in Congress, Dr. Weldon was awarded the status of Fellow of the American College of Physicians in 2005.

In 2006, Dr. Weldon founded the Israel Allies Caucus in the U.S. House, formed to strengthen ties with Israel and help establish a safe and secure future for the people of Israel. In 2007, he partnered with Israeli Knesset member Benny Elon to create the International Israel Allies Caucus Foundation, or IIACF, an organization dedicated to strengthening Israel and preserving peace in the Middle East.

In 2008, Dr. Weldon left Congress and returned to MIMA, where he has been practicing for three and a half years. MIMA now comprises over 100 doctors in multiple locations.

While in Congress, Dr. Weldon was a founding member of “The Second Amendments”, a bi-partisan rock & country band that performed at Farm Aid, We-Fest and other events. He and fellow band members Representatives Thaddeus McCotter, Colin Peterson, Kenny Hulshof and John Porter entertained troops in Iraq and Afghanistan in 2005.

[aionlinemoney]

Saudi Arabia Aims to build $100 Billion Dollar Artificial Intelligence Giant

Saudi Arabia is a famous tourist country and the second-largest Oil production supplier in the world. It is located in the Middle East. Currently, Saudi Arabia is preparing a new project related to artificial intelligence with the support of $100 Billion US Dollars to develop a technological hub and make it superior in AI.

This country plans to invest heavily in data centers and startups to develop Artificial intelligence in Saudi Arabia and make the country a technological hub. The name of this Project is said to be ‘’Project Transcendence’’. This Project will encourage Tech Companies to invest their resources in the Country.

Saudi Arabia is working on a challenging project to use Artificial intelligence to transform different parts of its economy. This effort is part of their Vision 2030 plan, Their aim is to build a modern and innovation-based economy. By focusing on AI, Saudi Arabia hopes to become one of the world’s top technological leaders.

Why 100 Billion Dollar? The Scale of Saudi Arabia

The $100 Billion number represents one of the largest single-country AI investments globally. For a factor, this investment would surpass the GDP of several countries, showing the Kingdom’s commitment to establishing itself as a technological superpower. But why such a vast investment?

The huge funding aims to put a complete foundation for Artificial intelligence integration across all sectors in Saudi Arabia. The Kingdom envisions using AI for innovations ranging from independent transportation and telemedicine to advanced data analytics in industries like oil and gas. Which are central to the Saudi economy. Additionally, the investment is likely to encourage AI-driven startups, creating a dynamic and energetic ecosystem of innovation and collaboration between all the sectors. Project Transcendence aims to expand by giving help to tech companies to generate capital and infrastructure, this will be a great deal for all the companies to grow in Saudi Arabia.

Rivalry with UAE: A New Chapter in the Middle East’s Tech Ambition: 

The UAE (United Arab Emirates) has long held the Top as the Middle East’s tech and innovation hub, with its capital Dubai placing itself as a smart city colonist and an AI-forward city. In recent years, the UAE has attracted major foreign investment, hosted global tech events, and launched various Artificial intelligence actions to make it a global AI leader.

The friendly competition between the UAE and Saudi Arabia could benefit the whole region by driving growth in Artificial Intelligence and technology, creating new jobs, and encouraging countries to work together. This rivalry can also attract global tech companies, researchers, and entrepreneurs who want to be part of the Middle East’s tech boom.

Building the Infrastructure for AI Success:

Saudi Arabia is investing more in building the foundation needed for Artificial Intelligence growth.

Much of this investment will focus on creating advanced infrastructure like high-speed data centers, cloud computing facilities, and research centers. The big part of this plan is NEOM, a huge 500 billion dollar city designed with AI as its central feature. NEOM will be displayed as a smart city technology, serving as a model of how cities can use Artificial intelligence to improve daily life.

NEOM city will include self-driving transportation, healthcare systems powered by AI, and green energy. As a high-tech city, it will also test advanced robots, smart devices, and many more. The NEOM city aims to show how Artificial Intelligence can improve city life and sustainability, attracting tech companies, researchers, and investors looking to the future.

Ethicals Considerations: 

Saudi Arabia AI plan will also focus on ethical issues and set up rules to guide safe and responsible AI use. As Artificial intelligence grows, it can bring challenges like privacy risks, data security concerns, and job changes. To handle this, Saudi Arabia aims to create rules that support innovation while making sure AI is used responsibly.

Conclusion: A Step Towards High-tech Future

Saudi Arabia massive $100 billion AI investment shows its dedication to becoming a global leader in artificial intelligence. This will help grow its economy in new ways and make it better in technology, both in the Gulf region and worldwide. By building a strong AI network and modern infrastructure, Saudi Arabia plans to transform its economy, and society, and lead the Middle East into a new age of AI innovation. As Saudi Arabia and the UAE compete to lead in AI, the Middle East could become a major global tech hub, advancing what AI can do. Always keep updated your knowledge related to Artificial intelligence and technology, Read AI related blog and News at AiOnlineMoney.

#aionlinemoney.com

[upcomingtradera]