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Panel Discussion: The Impact of AI in Precision Oncology

About This Webinar

Precision oncology benefits from a wide array of data modalities, including genomics, clinical information, imaging data, pathological findings, and real-world evidence. Integrating and analyzing these diverse datasets enables a holistic understanding of cancer biology, enhances treatment decision-making, supports the development of novel therapies, and ultimately leads to improved outcomes for cancer patients.

Join us for a unique opportunity to revisit a compelling panel discussion featuring healthcare visionaries, originally held at NASDAQ Headquarters on September 26, 2023. Our panelists will delved into the intricate landscape of AI's impact on transforming access to precision therapies, validating research outcomes, refining treatment approaches, and advancing our comprehension of cancer biology.

Register now to be a part of this event.

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Agenda
  • Opportunities of AI integration in healthcare
  • Regulatory processes and ethical implications
  • Current uses of AI in clinical practices and research
Who can view: Everyone
Webinar Price: Free
Featured Presenters
Webinar hosting presenter
Chief BioPharma Officer, SOPHiA GENETICS
Webinar hosting presenter
Medical Oncologist, Director of Liquid Biopsy Technologies & Genomics, MSK
Webinar hosting presenter
Medical Director, Precision Medicine Program & Clinical Trials, Henry Ford Health
Webinar hosting presenter
Head of Hematology & Oncology Data Sciences, R&D, Janssen
Webinar hosting presenter
SVP, Global Head of Oncology, Medical, AstraZeneca
Webinar hosting presenter
Chief Medical Officer & VP Healthcare, Microsoft
Hosted By
SOPHiA GENETICS webinar platform hosts Panel Discussion: The Impact of AI in Precision Oncology
SOPHiA GENETICS (Nasdaq: SOPH) is a healthcare technology company revolutionizing data-driven medicine and life sciences research. Their flagship product, the SOPHiA DDM™ Platform, empowers over 750 global institutions with cloud-based analytics and insights from diverse diagnostic datasets.
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