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How AI is transforming hematologic oncology

Episode 333 of the VJHemOnc Podcast podcast, hosted by VJHemOnc, titled "How AI is transforming hematologic oncology" was published on March 27, 2026 and runs 20 minutes.

March 27, 2026 ·20m · VJHemOnc Podcast

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This VJHemOnc podcast explores how artificial intelligence (AI) is transforming hematologic oncology, from clinical research and diagnostics to risk prediction and therapy development. Aaron Gerds, MD, Cleveland Clinic, Cleveland, OH, discusses AI-driven approaches to improving clinical trial enrollment, while Stephen Ansell, MD, PhD, Mayo Clinic, Rochester, MN, highlights advances in AI-based pathology for lymphoma classification. Ciara Freeman, MD, PhD, Moffitt Cancer Center, Tampa, FL, examines multimodal AI for predicting CAR T-cell outcomes, while Zinaida Good, PhD, Stanford University, Stanford, CA, and Andrea Schmidts, MD, Technical University of Munich, Munich, Germany, explore AI applications in CAR T-cell design. Gianluca Asti, MSc, Humanitas Clinical and Research Center, IRCCS, Rozzano, Italy, discusses federated learning for data sharing, and Amin Turki, MD, PhD, Ruhr-University Hospital Bochum and University Hospital Essen, Essen, Germany, highlights challenges in real-world AI implementation.

This VJHemOnc podcast explores how artificial intelligence (AI) is transforming hematologic oncology, from clinical research and diagnostics to risk prediction and therapy development. Aaron Gerds, MD, Cleveland Clinic, Cleveland, OH, discusses AI-driven approaches to improving clinical trial enrollment, while Stephen Ansell, MD, PhD, Mayo Clinic, Rochester, MN, highlights advances in AI-based pathology for lymphoma classification.

Ciara Freeman, MD, PhD, Moffitt Cancer Center, Tampa, FL, examines multimodal AI for predicting CAR T-cell outcomes, while Zinaida Good, PhD, Stanford University, Stanford, CA, and Andrea Schmidts, MD, Technical University of Munich, Munich, Germany, explore AI applications in CAR T-cell design. Gianluca Asti, MSc, Humanitas Clinical and Research Center, IRCCS, Rozzano, Italy, discusses federated learning for data sharing, and Amin Turki, MD, PhD, Ruhr-University Hospital Bochum and University Hospital Essen, Essen, Germany, highlights challenges in real-world AI implementation.

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