Prediction of blood test values under different lifestyle scenarios using time-series electronic health record.

ABSTRACT: Owing to increasing medical expenses, researchers have attempted to detect clinical signs and preventive measures of diseases using electronic health record (EHR). In particular, time-series EHRs collected by periodic medical check-up enable us to clarify the relevance among check-up results and individual environmental factors such as lifestyle. However, usually such time-series data have many missing observations and some results are strongly correlated to each other. These problems make the analysis difficult and there exists strong demand to detect clinical findings beyond them. We focus on blood test values in medical check-up results and apply a time-series analysis methodology using a state space model. It can infer the internal medical states emerged in blood test values and handle

SUBMITTER: Hasegawa T 

PROVIDER: S-EPMC7083324 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature