Since February of last year, tens of thousands of patients hospitalized at one of Minnesota's largest health systems have had their discharge planning decisions informed with help from an artificial intelligence model. But few if any of those patients has any idea about the AI involved in their care. That's because frontline clinicians at M Health Fairview generally don't mention the AI whirring behind the scenes in their conversations with patients. Unlock this article by subscribing to STAT Plus and enjoy your first 30 days free! STAT Plus is STAT's premium subscription service for in-depth biotech, pharma, policy, and life science coverage and analysis. Our award-winning team covers news on Wall Street, policy developments in Washington, early science breakthroughs and clinical trial results, and health care disruption in Silicon Valley and beyond.
Artificial intelligence-focused health care companies raised nearly $1 billion in funding in the first quarter of 2020, according to a new report from data analytics firm CB Insights, reflecting a growing trend in health tech: As much of the world braces for a probable pandemic-era recession, some health startups are nailing crucial, if eleventh-hour, funding. But it was a welcome uptick from the final quarter of last year, when funding dipped for the first time all year. Unlock this article by subscribing to STAT Plus and enjoy your first 30 days free! STAT Plus is STAT's premium subscription service for in-depth biotech, pharma, policy, and life science coverage and analysis. Our award-winning team covers news on Wall Street, policy developments in Washington, early science breakthroughs and clinical trial results, and health care disruption in Silicon Valley and beyond.
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations.
Franz Inc., in partnership with Montefiore Health System, is bringing the data lake to health IT using Franz's semantic graph database technology. Until its venture into the healthcare and pharmaceutical industries over the past few years, the 31-year-old Oakland, Calif., company had done business mainly in the worlds of national defense and intelligence, into which it sold its artificial intelligence-based triple store database that uses semantic, instead of relational, database technology. The system Franz has adapted for health IT, with partners such as Montefiore in the Bronx, N.Y., is based on AllegroGraph, one of its flagship products. Montefiore is using the system, called the Semantic Data Lake for Healthcare, to perform sophisticated predictive analytics in a quest to improve patient care and lower hospital costs. AllegroGraph uses the resource description framework (RDF) standard known as a "triple" to process and represent data semantically, and graph visualization software for visual discovery.