Artificial intelligence (AI) is making computer systems capable of executing human brain
tasks in many fields in all aspects of daily life. The enhancement in information and …

Abstract Background For some SARS-CoV-2 survivors, recovery from the acute phase of the
infection has been grueling with lingering effects. Many of the symptoms characterized as …

This study aims to predict death after COVID-19 using only the past medical information
routinely collected in electronic health records (EHRs) and to understand the differences in …

Summary Background Alzheimer's Disease (AD) is a complex clinical phenotype with
unprecedented social and economic tolls on an ageing global population. Real-world data …

The COVID-19 pandemic has devastated the world with health and economic wreckage.
Precise estimates of adverse outcomes from COVID-19 could have led to better allocation of …

Objective: Audit logs in electronic health record (EHR) systems capture interactions of
providers with clinical data. We determine if machine learning (ML) models trained using …

Objective The increasing translation of artificial intelligence (AI)/machine learning (ML)
models into clinical practice brings an increased risk of direct harm from modeling bias; …

Abstract Objective The Consortium for Clinical Characterization of COVID-19 by EHR (4CE)
is an international collaboration addressing coronavirus disease 2019 (COVID-19) with …

Objective High-throughput electronic phenotyping algorithms can accelerate translational
research using data from electronic health record (EHR) systems. The temporal information …

Objective Modern healthcare data reflect massive multi-level and multi-scale information
collected over many years. The majority of the existing phenotyping algorithms use case …