David S. McClintock

Mayo Clinic — United States

Computer Science · Physical Sciences

19h-index3.8kcitations50works1.92yr avg
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Research Topics

AI in cancer detection(20), Artificial Intelligence in Healthcare and Education(10), Clinical Laboratory Practices and Quality Control(7), Radiomics and Machine Learning in Medical Imaging(7), Mitochondrial Function and Pathology(6)

Publications49 total

Lymphovision: A lymphoma-specialized foundation model for histology-based lymphoma classification and subtyping
Blood·2025Open Access
Establishing a comprehensive artificial intelligence lifecycle framework for laboratory medicine and pathology: A series introduction
American Journal of Clinical Pathology·2025· 2 cited
Replicability of large-scale studies in computational pathology
2025
Contributors
Elsevier eBooks·2024Open Access
Artificial intelligence model development, deployment, and regulatory challenges in anatomic pathology
Elsevier eBooks·2024
An AI Model (LORIS) to Predict Immune Checkpoint Blockade Response in Cancer: A Clinical Data Science Perspective
Clinical Chemistry·2024Open Access
Embedding Internal Accountability Into Health Care Institutions for Safe, Effective, and Ethical Implementation of Artificial Intelligence Into Medical Practice: A Mayo Clinic Case Study
Mayo Clinic Proceedings Digital Health·2024· 10 citedOpen Access
Bridging the Clinical-Computational Transparency Gap in Digital Pathology
Archives of Pathology & Laboratory Medicine·2024· 3 citedOpen Access
Clinical AI model translation and deployment: creating a scalable, standardized, and responsible AI lifecycle framework in healthcare
2024· 1 cited
Artificial intelligence and digital pathology: clinical promise and deployment considerations
Journal of Medical Imaging·2023· 37 citedOpen Access
A clinical laboratorian’s journey in developing a machine learning algorithm to assist in testing utilization and stewardship
Journal of Laboratory and Precision Medicine·2023Open Access
Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade
EBioMedicine·2023· 97 citedOpen Access
Cybersecurity and Information Assurance for the Clinical Laboratory
The Journal of Applied Laboratory Medicine·2023· 24 citedOpen Access
Organizational preparedness for the use of large language models in pathology informatics
Journal of Pathology Informatics·2023· 28 citedOpen Access
Clinical Laboratory Informatics and Analytics: Challenges and Opportunities
Clinical Chemistry·2022· 3 citedOpen Access
The Roadmap to Interoperability and Laboratory Data: Current State and Next Steps
The Journal of Applied Laboratory Medicine·2022· 1 cited
The future of computational pathology: expectations regarding the anticipated role of artificial intelligence in pathology by 2030
2022· 3 citedOpen Access
Are You Prepared? Laboratory Downtime in the Ransomware Era
American Journal of Clinical Pathology·2022· 3 citedOpen Access
PATHOLOGIST-FREE TECHNICAL VALIDATION OF DISPLAYS FOR DIGITAL PATHOLOGY: A PROPOSAL FOR LIBERATING DISPLAYS FROM THE PIXEL PATHWAY
Journal of Pathology Informatics·2022Open Access
Quantitative Image Analysis as an Adjunct to Manual Scoring of ER, PgR, and HER2 in Invasive Breast Carcinoma
American Journal of Clinical Pathology·2021· 23 cited
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Frequent Co-authors

Roy E. Lee(10), Ulysses J. Balis(9), John R. Gilbertson(9), Jerome Cheng(8), Navdeep S. Chandel(7), Bruce A. Beckwith(7), Liron Pantanowitz(6), Toby C. Cornish(6), William J. Lane(6), Jason M. Baron(6), Frank C. Kuo(6), G. R. Scott Budinger(5), Jacob T. Abel(5), Bruce Levy(5), Veronica Klepeis(5), Steven N. Hart(4), Victor Brodsky(4), Maristela L. Onozato(4), Anand S. Dighe(4), Matthew T. Santore(3)