Mark D. Zarella
Associate Professor of Pathology and Laboratory Medicine at the Hospital of the University of PennsylvaniaPerelman School of Medicine at the University of Pennsylvania
Contact InformationHospital of the University of Pennsylvania
Department of Pathology and Laboratory Medicine
Philadelphia, PA, 19104
Email: mark.zarella@pennmedicine.upenn.edu
Specialty Division
Anatomic Pathology
Education
B.S. (Physics), University of Massachusetts Dartmouth, 2002
Ph.D. (Neuroscience ), State University of New York – Upstate Medical University, Syracuse, NY, 2011
Specialty Certification
Postgraduate Training
Postdoctoral Fellow – Neurobiology & Anatomy, University of Rochester Medical Center, Rochester, NY, 2011-2012
Awards and Honors
Clinical and Translational Research Institute Award, Drexel University College of Medicine, 2014
Professional Enhancement and Growth (PEG) Award, Drexel University College of Medicine, 2016
Elias Abrutyn Excellence in Mentorship Award, Drexel University College of Medicine, 2017
Drexel Libraries Data Science Fellow, Drexel University, 2019
Drexel Faculty Leadership Fellow, Drexel University College of Medicine, 2019
Memberships and Professional Organizations
Society for Neuroscience, 2003 - 2012
Digital Pathology Association, 2013 - Present
United States and Canadian Academy of Pathology, 2014 - Present
Association for Pathology Informatics, 2014 - Present
Commonwealth of Pennsylvania, 2017 - 2018
SPIE - The International Organization for Optics and Photonics, 2017 - Present
College of American Pathologists, 2019 - Present
IEEE Engineering in Medicine and Biology Society, 2019 - Present
Mitacs Elevate (Canada), 2019 - 2019
American Medical Informatics Association, 2019 - Present
United States Veterans Affairs, 2020 - 2021
National Research Data Infrastructure (Germany), 2021 - 2021
College of American Pathologists Foundation, 2022 - 2022
State University of New York, Upstate Medical University, 2022 - 2022
National Institute of Neurological Disorders and Stroke, 2023 - 2023
International Society for Computational Biology, 2023 - 2024
National Science Foundation, 2024 - 2024
Mitacs Accelerate (Canada), 2024 - 2025
Pennsylvania Association of Pathologists, 2025 - Present
Society for Imaging Informatics in Medicine, 2025 - Present
National Cancer Institute, 2025 - 2025
American Association of Physicists in Medicine, 2026 - Present
Web Links
Selected Publications
Recommendations for Performance Evaluation of Machine Learning in Pathology: A Concept Paper From the College of American Pathologists.
Hanna MG, Olson NH, Zarella M, Dash RC, Herrmann MD, Furtado LV, Stram MN, Raciti PM, Hassell L, Mays A, Pantanowitz L, Sirintrapun JS, Krishnamurthy S, Parwani A, Lujan G, Evans A, Glassy EF, Bui MM, Singh R, Souers RJ, de Baca ME, Seheult JN., Arch Pathol Lab Med. 148(10): e335-e361, 2024, PMID:38041522
Artificial intelligence and digital pathology: clinical promise and deployment considerations.
Zarella MD, McClintock DS, Batra H, Gullapalli RR, Valante M, Tan VO, Dayal S, Oh KS, Lara H, Garcia CA, Abels E., J Med Imaging (Bellingham) 10(5): 051802, 2023, PMID:37528811
High-throughput whole-slide scanning to enable large-scale data repository building.
Zarella MD, Rivera Alvarez K., J Pathology 257(4): 383-390, 2022, PMID:35511469
Continuing undergraduate pathology medical education in the coronavirus disease 2019 (COVID-19) global pandemic: The Johns Hopkins virtual surgical pathology clinical elective.
White, M., Birkness, J. E., Salimian, K. J., Meiss, A. E., Butcher, M., Davis, K., Ware, A. D., Zarella, M. D., Lecksell, K., Rooper, L. M., Cimino-Mathews, A., VandenBussche, C. J., Halushka, M. K.,Thompson, E. D., Archives of Pathology & Laboratory Medicine 145(7): 814–820, 2021
A practical guide to whole-slide imaging: A white paper from the Digital Pathology Association.
Zarella, M. D., Bowman, D. S., Aeffner, F., Farahani, N., Xthona, A., Absar, S. F., Parwani, A. V., Bui, M., & Hartman, D. J., Archives of Pathology & Laboratory Medicine 143(2): 222–234, 2019
Computational pathology definitions, best practices, and recommendations for regulatory guidance: A white paper from the Digital Pathology Association.
Abels, E., Pantanowitz, L., Aeffner, F., Zarella, M. D., van der Laak, J., Bui, M., Venkata, N., Parwani, A., Gibbs, J., Agosto-Arroyo, E., Beck, A., & Kozlowski, C., The Journal of Pathology 249(3): 286–294, 2019
IHCScoreGAN: An unsupervised generative adversarial network for end-to-end Ki67 scoring for clinical breast cancer diagnosis.
Molnar, C., Tavolara, T. E., Garcia, C. A., McClintock, D. S., Zarella, M. D., & Han, W., Proceedings of The 7th International Conference on Medical Imaging with Deep Learning 250(no issue): 1011-1025, 2024
BCL-2 expression aids in the immunohistochemical prediction of the Oncotype DX breast cancer recurrence score.
Zarella, M. D., Heintzelman, R. C., Popnikolov, N. K., & Garcia, F. U., BMC Clinical Pathology 18(1): 14, 2018
