Patient journey through cases of depression from claims database using machine learning algorithms.

ABSTRACT: Health insurance and acute hospital-based claims have recently become available as real-world data after marketing in Japan and, thus, classification and prediction using the machine learning approach can be applied to them. However, the methodology used for the analysis of real-world data has been hitherto under debate and research on visualizing the patient journey is still inconclusive. So far, to classify diseases based on medical histories and patient demographic background and to predict the patient prognosis for each disease, the correlation structure of real-world data has been estimated by machine learning. Therefore, we applied association analysis to real-world data to consider a combination of disease events as the patient journey for depression diagnoses. However, association

SUBMITTER: Kitanishi Y 

PROVIDER: S-EPMC7886120 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature