Health IT Analytics June 19, 2020
A machine learning technique can track patients’ EHR data over time to predict their risk of developing different diseases.
A new sequential approach uses machine learning to connect patients’ EHR data, including medications and diagnoses, to quantify disease risk, according to a study published in Cell Patterns.
While EHRs contain important information about patients’ health conditions and the care they receive, these records are not always precise. EHRs may not be direct indicators of patients’ true health states at different points in time, but rather reflect clinical processes, patients’ interactions with the system, and the recording process.
Researchers from Massachusetts General Hospital developed a strategy that uses machine learning to collect information on patients’ diagnoses and medications over time, rather...