Medial EarlySign: machine learning for population health (podcast)

https://healthbb.files.wordpress.com/2017/07/hbdew057-david-e-williams-interviews-medials-tomer-amit.mp3
Medial EarlySign analyzes standard EHR data to identify individuals at high risk for disease. The company’s first solution, ColonFlag uses longitudinal blood test data to identify patients who are at high risk for colorectal cancer.
I spoke recently with Medial executive Tomer Amit, who filled me in on the company’s approach and explained why the company has been named a Cool Vendor in AI by Gartner.

(0:15) What unmet need are you serving?
(1:05) You talk about using data that’s already available. What kind of data?
(3:02) When you mention “historical data” are you talking about longitudinal data for an individual patient or aggregated data for a population?
(4:18) Why is colorectal cancer an initial focus for the company, with your ColonFlag solution?
(5:13) Does ColonFlag replace colonoscopy or encourage someone to get one if they have an indicator that they are at greater risk?
(6:38) I see how it could help an individual. Would it actually help at the population level?
(7:45) You started in Israel and the EU, which have strong longitudinal medical records. Can the approach be applied in the US where that’s not the case?
(10:41) You have run your tests in different places around the world. Does the model differ by population or is there a universal algorithm?
(12:10) How do you protect your intellectual property? Once you are out the...

Source: Health Business Blog - July 7, 2017 Category: Health Management Authors: dewe67 Tags: Entrepreneurs International Technology Israel machine learning Source Type: blogs