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
Expanded Physiological Testing of the Lower Urinary Tract in Asymptomatic Women and Those With Urgency Urinary Incontinence: Findings From the LURN-Organ Study.
Journal Article Neurourology and urodynamics · June 2025 PurposeTo investigate sensory and motor function of the bladder and urethra in women with and without urgency urinary incontinence (UUI).Materials and methodsTreatment-seeking women with UUI and healthy, asymptomatic, nontreatment seeking ... Full text CiteStructural Changes in Brain White Matter Tracts Associated With Overactive Bladder Revealed by Diffusion Tensor Magnetic Resonance Imaging: Findings From a Symptoms of Lower Urinary Tract Dysfunction Research Network Cross-Sectional Case-Control Study.
Journal Article J Urol · August 2024 PURPOSE: Our objective was to investigate structural changes in brain white matter tracts using diffusion tensor imaging (DTI) in patients with overactive bladder (OAB). MATERIALS AND METHODS: Treatment-seeking OAB patients and matched controls enrolled in ... Full text Link to item CiteSoft phenotyping for sepsis via EHR time-aware soft clustering.
Journal Article J Biomed Inform · April 2024 OBJECTIVE: Sepsis is one of the most serious hospital conditions associated with high mortality. Sepsis is the result of a dysregulated immune response to infection that can lead to multiple organ dysfunction and death. Due to the wide variability in the c ... Full text Link to item CiteRecent Grants
Deprescribing 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 - 2029Predicting phenotypes in benign urology
ResearchCo Investigator · Awarded by National Institute of Diabetes and Digestive and Kidney Diseases · 2024 - 2027View All Grants
Education, Training & Certifications
University of Illinois ·
1993
Ph.D.