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Health Catalyst unveils AI tool that 'borrows from Amazon and Netflix'

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Health Catalyst introduced Touchstone at HIMSS18 and, in so doing, described it as a performance discovery, prioritization, benchmarking and recommendation tool. "Touchstone is built from the ground up on the latest AI and software from Silicon Valley," said Dale Sanders, President of Technology, Health Catalyst. "Touchstone's recommendation engine, which borrows from Amazon and Netflix, gives you not just comparative benchmarks but recommendations to improve your performance against benchmarks." The technology includes risk models based on artificial intelligence and anomaly detection algorithms that hospitals can use to pinpoint underperforming areas. Touchstone performs risk-adjusted benchmarking by culling data in claims, cost-accounting systems, EHRs, external benchmarks and operations to risk-adjust benchmarking, to "guide users to the data and analyses of greatest relevance to their work and to the organization's goals," the company said.


Exploring data with pandas and MapD using Apache Arrow

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At MapD, we've long been big fans of the PyData stack, and are constantly working on ways for our open source GPU-accelerated analytic SQL engine to play nicely with the terrific tools in the most popular stack that supports open data science. We are founding collaborators of GOAI (the GPU Open Analytics Initiative), working with the awesome folks at Anaconda and H2O.ai, and our friends at NVIDIA. In GOAI, we use Apache Arrow to mediate efficient, high-performance data interchange for analytics and AI workflows.


AI Demystified: Shaping the future for positive change

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The debate between Mark Zuckerberg and Elon Musk on the misunderstandings of artificial intelligence (AI) has brought to the forefront concerns and dangers of a robot takeover. Often misrepresented and misunderstood, AI continues to serve as a source of significant intrigue. It has long been lauded as the future of work, but according to notable Hollywood movies, is also a harbinger of a robot takeover.


Artificial intelligence can predict which congressional bills will pass

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Artificial intelligence can predict the behavior of Congress. The health care bill winding its way through the U.S. Senate is just one of thousands of pieces of legislation Congress will consider this year, most doomed to failure. Indeed, only about 4% of these bills become law. So which ones are worth paying attention to? A new artificial intelligence (AI) algorithm could help.


How AI can cut health care costs

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Companies spend a fortune to provide health insurance for their employees. In the U.S., 57 percent of all people get their health care through an employer-provided plan. In the past 10 years, employers have seen their costs increase over 63 percent, and costs are forecasted to grow at three times the inflation rate for the foreseeable future. Companies have begun shifting more of these costs to employees. The use of high-deductible health plans (HDHPs) by companies of all sizes just passed the 50 percent mark.


The Role of Artificial Intelligence in Patient Engagement

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Artificial intelligence (AI) has continued to make major headlines as part of the life sciences industry's trifecta of recent technology trends, and it's not hard to see why. Research published by MarketsandMarkets projected that the healthcare artificial intelligence market is expected to grow from $667.1 million in 2016 to more than $7.9 billion by 2022, a compound annual growth rate of 53 percent over the forecast period. This explains why companies such as IBM and Google are dominating advancements as they develop deep learning techniques that can revolutionize the way diseases are diagnosed, treated, and even prevented. However, with AI's success, comes its many challenges. According to Niall Brennan, former chief data officer at Centers for Medicare and Medicaid Services (CMS), one of the key challenges related to whether or not artificial intelligence and machine learning gain traction is "translating it into something tangible that will resonate with payers and lead them to think about realigning financial incentives" to improve patient outcomes and reduce healthcare costs.


How artificial intelligence is going to cure America's sick health care system

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For decades, technology has relentlessly made phones, laptops, apps and entire industries cheaper and better--while health care has stubbornly loitered in an alternate universe where tech makes everything more expensive and more complex. Now startups are applying artificial intelligence (AI), floods of data and automation in ways that promise to dramatically drive down the costs of health care while increasing effectiveness. If this profound trend plays out, within five to 10 years, Congress won't have to fight about the exploding costs of Medicaid and insurance. Instead, it might battle over what to do with a massive windfall. Today's debate over the repeal of Obamacare would come to seem as backward as a discussion about the merits of leeching. One proof point is in the maelstrom of activity around diabetes, the most expensive disease in the world.


In-Depth: AI in Healthcare- Where we are now and what's next

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The days of claiming artificial intelligence as a feature that set one startup or company apart from the others are over. These days, one would be hard-pressed to find any technology company attracting venture funding or partnerships that doesn't posit to use some form of machine learning. But for companies trying to innovate in healthcare using artificial intelligence, the stakes are considerably higher, meaning the hype surrounding the buzzword can be deflated far more quickly than in some other industry, where a mistaken algorithm doesn't mean the difference between life and death. Over the past five years, the number of digital health companies employing some form of artificial intelligence has dramatically increased. CB Insights tracked 100 AI-focused healthcare companies just this year, and noted 50 had raised their first equity rounds since January 2015.


New healthcare and population datasets now available in Google BigQuery Google Cloud Big Data and Machine Learning Blog Google Cloud Platform

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We've just added several publicly available healthcare datasets to the collection of public datasets on Google BigQuery (the cloud-native data warehouse for analytics at petabyte scale), including RxNorm (maintained by NLM) and the Healthcare Common Procedure Coding System (HCPCS) Level II. While it's not technically a healthcare dataset, we also added the 2000 and 2010 Decennial census counts broken down by age, gender and zip code tabular areas, which we hope will assist healthcare utilization and population health analysis (as we'll discuss below). Anyone with a Google Cloud Platform (GCP) account can explore these datasets. RxNorm was created by the U.S. National Library of Medicine (NLM) to provide a normalized naming system for clinical drugs and provide structured information such as brand names, ingredients and so on for each drug. Drug information is made available as a single "concepts" table while the relationships that map entities to each other (ingredient to brand name, for example) is made available as a separate "relationships" table.


In-Depth: AI in Healthcare- Where we are now and what's next

#artificialintelligence

The days of claiming artificial intelligence as a feature that set one startup or company apart from the others are over. These days, one would be hard-pressed to find any technology company attracting venture funding or partnerships that doesn't posit to use some form of machine learning. But for companies trying to innovate in healthcare using artificial intelligence, the stakes are considerably higher, meaning the hype surrounding the buzzword can be deflated far more quickly than in some other industry, where a mistaken algorithm doesn't mean the difference between life and death. Over the past five years, the number of digital health companies employing some form of artificial intelligence has dramatically increased. CB Insights tracked 100 AI-focused healthcare companies just this year, and noted 50 had raised their first equity rounds since January 2015.