PV24 Speakers

Subject to change.

 

 

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Anil Parwani, MD, PhD, MBA

Chair of Pathology, The Ohio State University


Dr. Anil Parwani is a Professor of Pathology and Biomedical Informatics at The Ohio State University. He serves as the Donald A. Senhauser Chair of the Department of Pathology and the Chief of Pathology Services for the Health System.. Dr Parwani has authored over four hundred peer-reviewed articles in major scientific journals and several books and book chapters. Dr. Parwani is the Editor-in-chief of Diagnostic Pathology and Co-editor of the Journal of Pathology Informatics.

 

 

SESSIONS

[ASDP] What's going on in the field of Digital Pathology and AI in Asia?
   Sun, Nov 3
   04:00PM - 05:00PM ET
  Regency O

Asia is a region of immense diversity, with distinct cultural, economic, and linguistic differences that present unique challenges and vast potential. Recently, countries like China, India, South Korea, Singapore, Australia, Dubai, and Japan have emerged as global leaders in science, yet Asia lags behind Europe and the U.S. in digital pathology and AI. To address this, the Asian Society of Digital Pathology (ASDP) was founded in Singapore in February 2024. ASDP aims to standardize practices, establish reference centers, and promote research and education across Asia. This session will introduce ASDP's vision and present findings from our large-scale survey on digital pathology in Asia, highlighting current trends and future potential. We will also host a panel discussion with ASDP leaders on strategies to maximize Asia's potential and explore collaborations with global organizations.

[Breakfast Sponsored by Epredia] Unlocking the Potential of Digital Pathology and AI: From Pixels to Diagnostics to Therapeutics
   Mon, Nov 4
   07:30AM - 08:30AM ET
  Regency R
PathAssist: Accelerating Dermatopathology Diagnosis with integrated Knowledge Graphs and LLMs
   Tue, Nov 5
   12:30PM - 12:50PM ET
  Regency Q

Learning Objectives

  1. Understand the different methods of data retrieval using AI.
  2. Learn the concept of building a Knowledge Graph from saved data.
  3. Harness the power of modern technologies for making better and faster diagnosis.
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