Cyft | Blog
The expression “big data” leads to some pretty reasonable assumptions: 1) you need huge volumes of data for machine learning and 2) more is more. Neither is particularly helpful in healthcare. We usually deal with smaller sets of rich but messy data (sample sizes in the hundreds or thousands). 10k rows vs 10M rows of claims data tend to
IBM sort of seemed like they were asking for it. From their claims to revolutionize cancer care in two years to their multi-billion $ growth projections, they worked real hard to project as healthcare's knight in shining armor. Of course, those inside of healthcare have seen many such knights burned to a crisp by the healthcare dragon -
I asked LinkedIn friends to submit their questions related to AI in healthcare in preparation for an upcoming keynote at this year's HIMSS in Vegas. I promised to try to answer the questions they submitted. This one is courtesy of my friend, the great Aman Bhandari and it garnered the most "likes." Here's his question: "I have asked for this several times and haven't
When journalists write about the disruptive power of artificial intelligence in healthcare they tend to zero in on radiology and pathology and for good reason. Both trades involve the interpretation of patterns from quantifiable image data - a thing that AI has proven highly capable of in several studies and commercial applications from facial recognition to the classification of hotdogs.
The healthcare AI space is frothy. Billions in venture capital are flowing, nearly every writer on the healthcare beat has at least an article or two on the topic, and there isn’t a medical conference that doesn’t at least have a panel if not a dedicated day to discuss. The promise and potential is very real.And yet, we seem to
A more technical post for those evaluating risk scores for care management, coupled with a real-world example. As healthcare organizations move toward taking on greater financial risk for keeping people healthy, it is critical for organizations to match people to the interventions they’re most likely to benefit from. This has traditionally been done by applying risk scores that are based on