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Machine learning: Changing everything but healthcare


Machine learning has proven it can beat traditional human techniques in healthcare for some time now, yet it remains limited in use in the healthcare industry. But that may be about to change. "Machine learning is changing everything -- except maybe healthcare," MIT professor John Guttag said here at the Big Data and Healthcare Analytics Forum on Oct. 24. While machine learning drives products and services such as Google Maps, many websites' tracking of shopping habits and presenting options, banking, credit card companies and others, healthcare providers have done much less with the existing technologies. "There's lots of talk, but very little action, very little progress in healthcare," Guttag said.

The Value Of Pairing Machine Learning With EMRs


Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare. According to Leonard D'Avolio, the healthcare industry has tools at its disposal, known variously as AI, big data, machine learning, data mining and cognitive computing, which can turn the EMR into a platform which supports next-gen value-based care.

Machine learning will replace human radiologists, pathologists, maybe soon


Artificial intelligence, machine learning and cognitive computing systems will replace a number of human jobs, even those requiring higher education, including doctors. "The numbers suggest that machine learning is happening," Leonard D'Avolio, CEO of Cyft, said at the Big Data & Healthcare Analytics Forum on Monday. "The opportunity has been sensed and the money is flowing." D'Avolio pointed specifically to radiology and pathology as ripe areas for machines to replace humans -- even suggesting that in the future it could become unethical not to do so. "In any part of healthcare where a human is interpreting data or images, when a computer does a better job than a human and costs less, the argument could be made that it would be wrong not to use a computer," D'Avolio said.

Machine Learning in Healthcare Takes Another Step data analytics, technology, readmissions, health plans, population health


Get ready for the next wave of predictive analytics, capable of identifying future admissions and health plan disenrollments. Until recently, many of the machine learning applications talked about for healthcare had been used to teach computing systems enough to be able to suggest a diagnosis on a specific disease. It essentially sent Watson to medical school. IBM had Watson ingest large amounts of medical literature to learn everything physicians are taught about patients' conditions, and then taught it to make diagnoses. But a Harvard professor who leads a startup supplying machine learning technology to Senior Whole Health, a Medicaid managed care organization active in New York state and Massachusetts, says that machine learning will eventually power all technologies we know today as predictive analytics and population health.

The mashup approach: How healthcare can save billions on AI and machine learning


Healthcare is at a two-tined fork: One strip leads to repeating the same mistakes others have already made while the more enlightened rail learns from those instead.