Drew Neavin

Infrared molecular fingerprinting of blood-based liquid biopsies for the detection of cancer

Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases

Stability of person-specific blood-based infrared molecular fingerprints opens up prospects for health monitoring

The role of artificial intelligence in healthcare: a structured literature review

Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

AI-assisted prediction of differential response to antidepressant classes using electronic health records

Single-cell eQTL models reveal dynamic T cell state dependence of disease loci

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

Metabolomics enables precision medicine: “A White Paper, Community Perspective”

Clinical multi-omics strategies for the effective cancer management

Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study

Physics-informed machine learning

Metabolomics for Investigating Physiological and Pathophysiological Processes

MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights

Pharmacogenomics‐Driven Prediction of Antidepressant Treatment Outcomes: A Machine‐Learning Approach With Multi‐trial Replication

Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings

TSPAN5, ERICH3 and selective serotonin reuptake inhibitors in major depressive disorder: pharmacometabolomics-informed pharmacogenomics

Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells

Pharmacometabolomics informs pharmacogenomics

Augmentation of Physician Assessments with Multi-Omics Enhances Predictability of Drug Response: A Case Study of Major Depressive Disorder