Inside Digital Health July 17, 2019
Artificial intelligence (AI) has found application in almost every industry today, but the stakes are arguably highest in healthcare because mistakes can affect patient care. The tsunami of health data being produced on a daily basis, along with chronic inefficiencies across the system, make the industry ripe for AI-driven innovation. However, the most significant hurdles in realizing AI’s full potential in healthcare is identifying the right applications and earning the trust of users.
A substantial portion of healthcare data generated today is unstructured, making it challenging to use to effectively train algorithms. Moreover, healthcare definitions and policies are constantly in flux. A machine learning (ML) model trained on data about diabetic patients, for example, would need to be adjusted every...
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