This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Objective Accurate and rapid phenotyping is a prerequisite to leveraging electronic health
records for biomedical research. While early phenotyping relied on rule-based algorithms …

Accurate early prediction of heart failure and identification of heart failure sub-phenotypes
can enable in-time interventions and treatments, assist with policy decisions, and lead to a …

There has been rapid growth in the use of artificial intelligence (AI) analytics in medicine in
recent years, including in rheumatic and musculoskeletal diseases (RMDs). Such methods …

Background The national increase in opioid use and misuse has become a public health
crisis in the US To tackle this crisis, the systematic evaluation and monitoring of opioid …

Obesity is a heritable disease, characterised by excess adiposity that is measured by body
mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known …

Burn injuries often result in a high level of clinical heterogeneity and poor prognosis in
patients with severe burns. Clustering algorithms, which are unsupervised methods that can …

Decision support systems are being developed to assist clinicians in complex decision-
making processes by leveraging information from clinical knowledge and electronic health …

The increase in availability of longitudinal EHR data is leading to improved understanding of
diseases and discovery of novel phenotypes. The majority of clustering algorithms focus …

Single-cell RNA sequencing (scRNA-seq) provides high-resolution information on
transcriptomic changes at the single-cell level, which is of great significance for …