Abstract
In recent years, there has been an increase in the automatic analysis of electronic health records (EHR) for the screening of diseases or the outcomes measurement. However, little has been done to assess the diversity of algorithms, databases, and analysis protocols. We aim to determine the global extend of machile learning (ML) use in screening diseasses by analyzing structure, demographics and clinical characteristics of EHR employed in previous analysis
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Paper version not known
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Paper Title
Journal
Date
