Note from Sean Khozin to Susan D'Elia, Can AI-Powered Medical Imaging Reclassifying Disease Categories? Let's Discuss at PMWC June 28-30 - PMWC Precision Medicine World Conference

Note from Sean Khozin to Susan D’Elia, Can AI-Powered Medical Imaging Reclassifying Disease Categories? Let’s Discuss at PMWC June 28-30

In recent years, we’ve made significant advances on the technology and algorithm development front, while old incentive structures and legacy organizational behaviors continue to represent the most critical barriers to unlocking the full potential of AI in biomedical research and healthcare delivery.

Adding the outputs of omics pipelines to AI-powered interpretation of medical imaging can give us a more complete understanding of mechanisms of disease in an objective and reproducible manner not limited by human judgement or variations in expertise and experience. This requires incentives to allow data sharing at scale, technologies for secure exchange of data while preserving patient privacy, and organizational constructs to accommodate new workflows.
– Sean Khozin, CEO, CancerLinQ & “AI Roadmap: Opportunities and Challenges” Session Chair, PMWC 2022 Silicon Valley June 28-30 (400 Speaker Program)

To address the pressing needs of revamping and optimizing existing processes and to accommodate changes in the clinical setting for evolving imaging technologies, we have created the AI in Medical Imaging Track which is chaired by Sharmila Majumdar (UCSF).

The various sessions include:
• Panel chaired by Sean Khozin (CancerLinQ): AI Roadmap: Opportunities and Challenges with Matthew Lungren (AWS), Patrick Loerch (Gilead), Daniel J. Arbess (Xerion Investments), Nigam Shah (Stanford), and Chris Gibson (Recursion).
• Actionable AI: Empowering the Stewards of Precision Medicine with Abdul Halabi (Tempus)
• Panel chaired by Sharmila Majumdar (UCSF): Technical Advancements in Clinical Machine Learning – What’s New in 2022 with Matthew Lungren (AWS), Jayashree Kalpathy-Cramer (Harvard University), and John Mongan (UCSF)
• Image Applications for Clinical Diagnosis with session Chair Esther L. Yuh (UCSF) and with Thorsten Fleiter (University of Maryland), Imon Banerjee (Mayo Clinic), Pratik Mukherjee (UCSF), and Lawrence Schwartz (Columbia University Medical Center)
• The Impact of AI and High-Resolution Digital Slide Imaging with Chair Juan C. Santa Rosario (Coreplus) and with Mariano de Socarraz (Coreplus)
• Panel chaired by Fatemeh Zabihollahy (UCLA): Evaluation of AI Software for Radiological Applications with Akshay Chaudhari (Stanford University), Mona Flores (NVIDIA), and Kilian Koepsell (Caption Health)

• More presenters in the PMWC 2022 AI & Data Sciences Showcases: Thomas Westerling-Bui, Aiforia; Eric Horler, AIQ Solutions; Amrie Grammer, AMPEL BioSolutions; Krzysztof Rataj, Ardigen; Timo Kanninen, BC Platforms; Shawnnah Monterrey, BeanStock Ventures; Shyam Banuprakash, Clario; Jarret Glasscock, Cofactor Genomics; Scott Hutton, Collaborative Drug; Maddison Masaeli, Deepcell; Jason Springs, Endpoint Health; Rafael Rosengarten, Genialis; Juan Harrison, IMIDomics; Sarah Jenna, MIMs; Christopher Williams, MMRF; Nicholas Wilson, nference; Hongxin Zhang, Memorial Sloan Kettering Cancer Center; Ruby Hsu, PathAI; Steve Gardner, PrecisionLife; Billy Amzal, QUINTEN HEALTH; Ryan Friese, Rosalind; William Oh, Sema4; Ofer Mendelevitch, Syntegra; Kaushik Chakravarty, VeriSIM Life; Susan Wood, VIDA.
Interested to Present in the Showcase? Reach out by 5/31.

Susan, Join this exclusive lineup of presenters and contributors today and learn firsthand at the in-person PMWC 2022 Silicon Valley June 28-30 conference what we need to do as a community to move the field of AI-enhanced imaging to the next stage.

I’m looking forward to welcoming you to the conference.


Tal Behar
Co-founder & President, PMWC
Precision Medicine World Conference – June 28-30, 2022 Silicon Valley

It’s easy to imagine in 10 years AI-powered medical imaging playing a pivotal role in not only helping physicians make more accurate diagnoses but also in reclassifying entire disease categories by going beyond what the human eye can see and much closer to the underlying mechanisms of disease.” – SK