Pratik Prashant Shah

Title(s)Assistant Professor, Pathology
SchoolSchool of Medicine
Address1001 Health Sciences Road
Irvine CA 92697-3950
Phone(949) 824-8576
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    -Faculty Member and Professor, Pathology, Director Computational Medicine Research Program, School of Medicine

    -Faculty Member and Professor, Biomedical Engineering, The Henry Samueli School of Engineering

    -Faculty Member and Professor, Electrical Engineering and Computer Science, The Henry Samueli School of Engineering

    Research Overview: Dr. Shah's lab focuses on hypothesis-driven deep learning, generative AI, biomedical engineering, and clinical research to develop technologies for diagnosing and treating cancer, infectious diseases, and neurological disorders. The research group combines and invents novel deep learning, biological, and statistical methods to tackle challenges in personalized medicine. Dr. Shah's work includes advancements in generating novel medical images for unbiased, patient-centered care, cancer diagnostics at the cellular level using companion diagnostic assays, and evaluating the impact of clinical decision-making on infectious diseases and antimicrobial therapy — all within a unified theoretical and methodological framework. Dr. Shah and his team are developing a dynamic, living-systems framework for computational medicine, transitioning from static models to real-time, systems-wide perspectives on molecular and clinical processes. Their goal is to invent and deploy equitable medical technologies that improve patient outcomes and public health.

    Short Bio: Dr. Pratik Shah is a professor at the University of California and holds tenure-track faculty appointments in the academic senate lines of Pathology & Laboratory Medicine, Electrical Engineering & Computer Science, and Biomedical Engineering. Recent work from his lab has been published in Cell Press, Nature Digital Medicine, Cell press, Journal of American Medical Association, leading machine learning conferences, and workshop proceedings of The National Academies of Science Engineering and Medicine. Previously, Dr. Shah was a Principal Investigator at the Massachusetts Institute of Technology (MIT), where he led a computational medicine program at the MIT Media Lab. He also served as the principal investigator for a memorandum of understanding with the U.S. FDA, aimed at establishing AI and machine learning research ecosystems for clinical development. Dr. Shah holds a BS, MS, and PhD in biological and data sciences and completed fellowship training at Massachusetts General Hospital, the Broad Institute of MIT and Harvard, and Harvard Medical School.

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    Virtual Digital Histopathology with Explainable Deep Learning for Prostate Diagnosis
    NIH/NCI R21Sep 1, 2024 - Aug 31, 2026
    Role: Principal Investigator

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    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Researchers can login to make corrections and additions, or contact us for help. to make corrections and additions.
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    Altmetrics Details PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. A deep-learning toolkit for visualization and interpretation of segmented medical images. Cell Rep Methods. 2021 11 22; 1(7):100107. Ghosal S, Shah P. PMID: 35474999; PMCID: PMC9017181.
      View in: PubMed   Mentions: 1     Fields:    Translation:Humans
    2. Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis. JAMA Netw Open. 2020 05 01; 3(5):e205111. Rana A, Lowe A, Lithgow M, Horback K, Janovitz T, Da Silva A, Tsai H, Shanmugam V, Bayat A, Shah P. PMID: 32432709; PMCID: PMC7240356.
      View in: PubMed   Mentions: 22     Fields:    Translation:Humans
    3. Artificial intelligence and machine learning in clinical development: a translational perspective. NPJ Digit Med. 2019; 2:69. Shah P, Kendall F, Khozin S, Goosen R, Hu J, Laramie J, Ringel M, Schork N. PMID: 31372505; PMCID: PMC6659652.
      View in: PubMed   Mentions: 109  
    4. Artificial Intelligence for Clinical Trial Design. Trends Pharmacol Sci. 2019 08; 40(8):577-591. Harrer S, Shah P, Antony B, Hu J. PMID: 31326235.
      View in: PubMed   Mentions: 130     Fields:    Translation:Humans
    5. Reinforcement Learning with Action-Derived Rewards for Chemotherapy and Clinical Trial Dosing Regimen Selection. Proceedings of Machine Learning Research. 2018; 85:161–226. Gregory Yauney, Pratik Shah. . View Publication.
    6. Technology-enabled examinations of cardiac rhythm, optic nerve, oral health, tympanic membrane, gait and coordination evaluated jointly with routine health screenings: an observational study at the 2015 Kumbh Mela in India. BMJ Open. 2018 04 20; 8(4):e018774. Shah P, Yauney G, Gupta O, Patalano Ii V, Mohit M, Merchant R, Subramanian SV. PMID: 29678964; PMCID: PMC5914894.
      View in: PubMed   Mentions: 4     Fields:    Translation:HumansPHPublic Health
    7. Detection of Biomarkers of Periodontal Disease in Human Saliva Using Stabilized, Vertical Flow Immunoassays. ACS Sens. 2017 11 22; 2(11):1589-1593. Yee EH, Lathwal S, Shah PP, Sikes HD. PMID: 29090909.
      View in: PubMed   Mentions: 15     Fields:    Translation:Humans
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