Mohammad K. Alexanderani, MD

Dr. Alexanderani is an Assistant Professor of Pathology at the University of Pittsburgh School of Medicine, within the Department of Pathology. He specializes in Computational Pathology and Artificial Intelligence at the Computational Pathology & AI Center of Excellence (CPACE). With a steadfast commitment to advancing the field of pathology, he leverages cutting-edge AI and machine learning technologies to unlock histopathological features—referred to as "Pathomics"—in digital images and detect novel patterns, ultimately developing next-generation diagnostic and theragnostic tools that enhance clinical practice. His innovative work focuses on optimizing diagnostic precision and treatment efficacy through integrating state-of-the-art AI tools in the clinical workflow, significantly enhancing patient outcomes through advanced precision pathology.

As a physician-scientist, Dr. Alexanderani has made significant contributions to the field, evidenced by numerous patents, grants, prestigious awards, book chapters, and publications in high-impact journals. He has delivered multiple platform and poster presentations, as well as invited lectures at national and international conferences, including conferences hosted by Digital Pathology Associations, the American Association for the Study of Liver Diseases, the Association of Pathology Informatics. In addition to the above efforts, Dr. Alexanderani is actively involved in severalleadership committees, including the Digital Anatomic Pathology Academy (DAPA), the Fibrosis & Cancer Special Interest Groups (SIG) of the American Association for the Study of Liver Diseases (AASLD), and serves as a social media ambassador for AASLD and the American Society for Clinical Pathology. Additionally, he is a reviewer for several scientific journals, including Crohn's & Colitis and the Journal of Pathology Informatics.

Dr. Alexanderani earned his medical degree from the Kasr Al-Ainy School of Medicine at Cairo University and completed several postdoctoral fellowships in diverse fields, including Gastroenterology and Hepatology, Pharmacology, and Immunology at the University of Louisville, as well as Clinical Informatics at Morehouse School of Medicine. He additionally underwent residency training in pathology at Geisinger Commonwealth School of Medicine before pursuing an advanced fellowship in Computational Pathology and AI as the inaugural fellow in the Pathologist-Scientist Track of the Next Generation Onco-Pathologists Program at Weill Cornell Medicine, where he received the prestigious NIH T32 Award

Honors & Awards

• Abstract selection for Digital Pathology Association track session oral presentation, Orlando, FL,2024
• Digital Pathology Association Exclusive Travel Award for Aspiring Pathology Leaders, Orlando, FL,2024
• iDEA-iTECH Award in Precision Medicine & Computational Biology- North America, Sanofi, 2024
• Special recognition as a cover featured publication in the Molecular Cancer Research Journal, 2024
• Top 50 Publications in Nature Communications for Life and Biological Sciences, 2023
• Ruth L. Kirschstein National Research Service Award for Next Generation Pathologists, 2022
• Stowell-Orbison Surgical Pathology Poster Presentation Session, USCAP, 2020 & 2021
• American Society of Clinical Pathology "40 Under Forty Honoree" 2020
• Pathologist in-Training Award, United States & Canadian Academy of Pathology Foundation, USCAP, LA, CA, 2019
• Distinction for Top-Scoring Abstract, Research Centers in Minority Institutions Network, Washington, DC, 2017
• Honorable Mention in AASLD Next Generation Liver Researchers' Spotlight and AASLD Bulletin, Boston, MA, 2016
• Abstract Award, Top 10% Abstracts, AASLD Scientific Committee, San Francisco, CA, 2015
• Presidential Poster of Distinction Award, AASLD, San Francisco, CA, 2015
• Young Investigator Award, AASLD Foundation, San Francisco, CA, 2015
• Abstract Award, Top 3 Abstracts, Digestive Disease Week-DDW, Washington, DC, 2015
• Fellow Travel Award for Plenary Session Lecture, Digestive Disease Week-DDW, Washington, DC, 2015
• Research Fellow Travel Award to AASLD, University of Louisville, School of Medicine, AASLD, Boston, MA, 2014
• Research Fellow Travel Award to DDW, University of Louisville, School of Medicine, DDW, San Diego, CA, 2012

Interests

Multimodal Machine Learning: Dr. Alexanderani works on applying multimodal machine learning that integrates pathological images with clinical laboratory and molecular data, as well as information from electronic medical records. He develops and deploys interpretable, state-of-the-art multimodal unsupervised deep learning models designed to enhance clinical decision-making. His work focuses on creating and validating clinically applicable tools that effectively stratify at-risk patients, thereby improving outcomes and advancing precision diagnostics.

Whole Slide Imaging Analysis. Dr. Alexanderani is utilizing cutting-edge AI algorithms to optimize the grading of diseases by quantifying histopathological findings, such as liver fibrosis, steatosis, and tumor stroma ratio, which are critical for timely and accurate patient management. His work aims to streamline laboratory processes, significantly improving turnaround times and enabling informed treatment decisions more swiftly.

Spatial Transcriptomics. Dr. Alexanderani is leveraging an advanced deep learning tissue classification approach in spatial transcriptomics to unleash the game-changing capabilities of this technology in pathology. He employs sophisticated computational and hybrid methods to analyze the molecular and spatial dynamics of the tumor microenvironment, integrating high-resolution spatial proteomics and transcriptomics with routine histopathology imaging data. This groundbreaking work introduces a new dimension to the histopathological landscape, enabling a more comprehensive and nuanced analysis of disease processes.

Healthcare Mobile Apps and Web Applications: Dr. Alexanderani is developing mobile applications that streamline the entry of laboratory test results by patients, effectively addressing gaps in healthcare delivery through enhanced follow-up during patient absences and promoting medication adherence. Additionally, he worked on creating an educational application for on-call consult electronic documentation, aimed at improving the transition of care and ensuring continuity in patient management. This dual approach not only empowers patients but also enhances the overall efficiency and effectiveness of healthcare services.