Background Depression is one of the most significant health conditions in personal, social,
and economic impact. The aim of this review is to summarize existing literature in which …

Diagnosing depression at an early stage is crucial and majorly depends on the clinician's
skill. The present work aims to develop an automated tool for assisting the diagnostic …

Background High-quality phenotype definitions are desirable to enable the extraction of
patient cohorts from large electronic health record repositories and are characterized by …

Federated Learning (FL) is a machine learning framework that enables multiple
organizations to train a model without sharing their data with a central server. However, it …

Objective To develop a standardizable, reproducible method for creating drug codelists that
incorporates clinical expertise and is adaptable to other studies and databases. Materials …

Objective To assess and compare electronic health record (EHR) documentation of chronic
disease in problem lists and encounter diagnosis records among Community Health Center …

Depression is a heterogeneous and complex psychological syndrome with highly variable
manifestations, which poses difficulties for treatment and prognosis. Depression patients are …

Background: The immediate use of data exported from electronic health records (EHRs) for
research is often limited by the necessity to transform data elements into an actual data set …

Objective To facilitate patient disease subset and risk factor identification by constructing a
pipeline which is generalizable, provides easily interpretable results, and allows replication …

Background Efforts to reduce the heterogeneity of major depressive disorder (MDD) by
identifying subtypes have not yet facilitated treatment personalization or investigation of …