Overview
David Page works on algorithms for data mining and machine learning, as well as their applications to biomedical data, especially de-identified electronic health records and high-throughput genetic and other molecular data. Of particular interest are machine learning methods for complex multi-relational data (such as electronic health records or molecules as shown) and irregular temporal data, and methods that find causal relationships or produce human-interpretable output (such as the rules for molecular bioactivity shown in green to the side).
Current Appointments & Affiliations
Duke Health Distinguished Professor of Biostatistics & Bioinformatics
·
2025 - Present
Biostatistics & Bioinformatics, Division of Biostatistics,
Biostatistics & Bioinformatics
Professor of Biostatistics & Bioinformatics
·
2021 - Present
Biostatistics & Bioinformatics, Division of Biostatistics,
Biostatistics & Bioinformatics
Professor of Computer Science
·
2021 - Present
Computer Science,
Trinity College of Arts & Sciences
Chair of Biostatistics & Bioinformatics
·
2019 - Present
Biostatistics & Bioinformatics, Division of Biostatistics,
Biostatistics & Bioinformatics
Recent Publications
Pathogenic Genomic Alterations in Circulating Tumor DNA Predict Overall Survival in Men with Metastatic Castrate-resistant Prostate Cancer.
Journal Article Eur Urol · April 2026 BACKGROUND AND OBJECTIVE: Although validated prognostic models exist for men with metastatic castration-resistant prostate cancer (mCRPC), current tools do not incorporate genomic biomarkers such as circulating tumor DNA (ctDNA) aneuploidy or pathogenic ge ... Full text Link to item CiteThe LURN Study-What Have We "LURN"ed So Far?
Journal Article Neurourology and urodynamics · April 2026 LURN was established by the NIDDK to study LUTS with a holistic approach, focusing on urinary urgency. LURN has developed patient-reported outcome instruments to better measure LUTS in men and women. LURN SI-29 can be used for clinical research. LURN SI-10 ... Full text CiteStratifying Risk and Treatment Benefit: A Model Predicting Overall Survival in Men with Metastatic De Novo Hormone-sensitive Prostate Cancer in Trials Investigating Docetaxel (the STOPCAP Collaboration).
Journal Article Eur Urol Focus · February 18, 2026 BACKGROUND AND OBJECTIVE: This study aimed to develop and validate a prognostic model for overall survival (OS) in men with de novo metastatic hormone-sensitive prostate cancer (mHSPC), using clinical factors from phase 3 trials to improve survival predict ... Full text Link to item CiteRecent Grants
Advancing a Holistic Understanding of Variability in Lived Experience with Sickle Cell Pain
ResearchCo-Principal Investigator · Awarded by National Institutes of Health · 2025 - 2030Deprescribing Decision-Making using Machine Learning Individualized Treatment Rules to Improve CNS Polypharmacy
ResearchCo Investigator · Awarded by National Institutes of Health · 2024 - 2029Integrated Detection and Classification of Sepsis via Tensor Methods Using EHR
ResearchCo Investigator · Awarded by National Heart, Lung, and Blood Institute · 2024 - 2029View All Grants
Education
University of Illinois ·
1993
Ph.D.