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JUL 18, 2023 3:30 PM EDT

Digital Pathology and Artificial Intelligence for Clinical Diagnostics: Current State and Future Directions

C.E. Credits: P.A.C.E. CE | Florida CE
Speaker
  • Anil Parwani, M.D., Ph.D., M.B.A.

    Professor of Pathology and Biomedical Informatics
    Vice-Chair of Anatomic Pathology
    Director of Pathology Informatics
    Director, Digital Pathology Shared Resources
    Principal Investigator, Cooperative Human Tissue Network (CHTN) Midwestern Division
    Wexner Medical Center - Department of Pathology
    The Ohio State University
    BIOGRAPHY

Abstract

The practice of pathology is rapidly undergoing a transformation in which multiple tools such as digital imaging, advanced artificial intelligence algorithms, and computer-aided diagnostic techniques are being linked with molecular pathology resulting in increased diagnostic power based on the ability of modern-day pathologists to use these new tools and to interpret the data generated by them. 

Automated whole slide imaging (WSI) scanners are now rendering diagnostic quality, high-resolution images of entire glass slides and combining these images with innovative AI-based decision support tools that are making it possible to integrate imaging into all aspects of pathology reporting including anatomical, clinical and molecular pathology. The recent approvals of WSI scanner for primary diagnosis by FDA as well as the approval of prostate Al algorithm has paved the way for starting to incorporate this exciting technology for use in primary diagnosis Once the slides are digitized, artificial intelligence and computational pathology tools will serve as a platform for innovations and advances in anatomical and clinical pathology in the future. This talk will describe where we are in the journey towards utilizing these tools for clinical diagnostics and what are the possibilities, once fully implemented.

Learning Objectives:

  • Outline an overview of the evolution of digital pathology and AI and its current state for clinical diagnostics, research and education
  • Identify the challenges and opportunities for implementing digital pathology and AI in the clinical areas using OSU as an example
  • Assess the future directions of Digital Pathology /Artificial Intelligence technology’s role in advanced diagnostics

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