Speaker Profile
Ph.D., Research Assistant Professor, Case Western Reserve
Biography
Dr. Rakesh Shiradkar is a research faculty in Biomedical Engineering at Case Western Reserve University. He obtained his PhD in Electrical and Computer Engineering from the National University of Singapore in 2014 and joined Case Western Reserve University as a post-doctoral researcher. His research focuses on developing machine learning and artificial intelligence methods in conjunction with quantitative and conventional MRI for image-based diagnosis and prognosis of prostate cancer. He also works on integrating multi-modal data such as MRI, pathology, genomics for developing reliable and robust methods for cancer diagnostics. He has also been exploring methods for addressing health disparities in prostate cancer using AI.
He has been leading multi-institutional projects on cancer diagnostics and is the PI on a 3 year DoD early career award and a Pilot Award from the Case Comprehensive Cancer Center. He has published extensively on prostate imaging AI in more than 20 high impact journals and conference proceedings.
Talk
Computational Imaging Biomarkers for Imaging based Cancer Diagnosis
Imaging plays a significant role in non-invasive diagnosis and assessment of cancer, but is limited by inter-observer variability and confounders. This talk will demonstrate the potential of computational imaging biomarkers in quantifying cancer heterogeneity for improving diagnosis and also prognosticating treatment outcomes from pre-treatment imaging.
Session Abstract – PMWC 2022 Silicon Valley
Track Chairs:
Sharmila Majumdar, UCSF
The use of Artificial Intelligence (AI) in diagnostic medical imaging is undergoing extensive evaluation. AI has shown impressive accuracy and sensitivity in the identification of imaging abnormalities and promises to enhance tissue-based detection and characterization. This track will explore technical advancements in clinical machine learning and use cases in radiology.
Sessions:
- AI Roadmap: Opportunities and Challenges (PANEL)
Session Chair: Sean Khozin, CancerLinQ
- Matthew Lungren, AWS
- Patrick Loerch, Gilead
- Greg Yap, Menlo Ventures
- Lydia The, McKinsey & Company
- Chris Gibson, Recursion
- Andrea Mazzocchi, Known Medicine - Actionable AI: Empowering the Stewards of Precision Medicine
- Martin Stumpe, Tempus - Technical Advancements in Clinical Machine Learning - What's New in 2022 (PANEL)
Session Chair: Sharmila Majumdar, UCSF
- Matthew Lungren, AWS - Jayashree Kalpathy-Cramer, Harvard
- John Mongan, UCSF - Image Applications for Clinical Diagnosis
Session Chair: Esther L. Yuh, UCSF
- Thorsten Fleiter, U. of Maryland
- Imon Banerjee, Mayo Clinic
- Pratik Mukherjee, UCSF
- Lawrence Schwartz, Columbia University Medical Center
- Rakesh Shiradkar, Case Western Reserve University - The Impact of AI and High-Resolution Digital Slide Imaging
Session Chair: Ryan Davis, Epredia
- Andy Moye, Paige
- Thomas Westerling-Bui, Aiforia
Session Chair: Fatemeh Zabihollahy, UCLA
- Mirabela Rusu, Stanford
- Mona Flores, NVIDIA
- Kilian Koepsell, Caption Health
- Eric Horler, AIQ Solutions
