Objective The UK Biobank provides a rich collection of longitudinal clinical data coming from
different healthcare providers and sources in England, Wales, and Scotland. Although …

Abstract Machine learning (ML) models trained for triggering clinical decision support (CDS)
are typically either accurate or interpretable but not both. Scaling CDS to the panoply of …

Background Stroke is an important clinical outcome in cardiovascular research. However,
the ascertainment of incident stroke is typically accomplished via time-consuming manual …

Outcome prediction aims to predict the future health condition of patients from Electronic
Health Record (EHR) data. Because of the sequential characteristic of EHR data, recurrent …

Introduction Immune checkpoint inhibitor-induced inflammatory arthritis (ICI-IA) poses a
major clinical challenge to ICI therapy for cancer, with 13% of cases halting ICI therapy and …

Clinical text classification of electronic medical records is a challenging task. Existing
electronic records suffer from irrelevant text, misspellings, semantic ambiguity, and …

Background Nowadays, patients with chronic diseases such as diabetes and hypertension
have reached alarming numbers worldwide. These diseases increase the risk of developing …

Background Many studies have evaluated stroke using claims data; most of these studies
have defined ischemic stroke using an operational definition following the rule-based …

Polygenic risk scores represent an individual's genetic susceptibility to a phenotype. Like
with any models, statistical models commonly employed to fit polygenic risk scores and …

Methods: We conducted a retrospective study of the electronic health records (EHRs) of 89
patients who developed ICI-IA out of 2451 cancer patients who received ICI therapy at …