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Had a great time at AACR AI conference sharing vignettes about our recent research 1) TxAgent - AI agent for therapeutic reasoning across a universe of tools. Start here to test TxAgent and submit your most challenging therapeutic questions: txagentevals.curebench.ai Shanghua Gao

A Canadian doctor explains the difference between the universal health care system in Canada, where everyone is covered and there are no out-of-pocket costs, and the American system where people go bankrupt in order to receive cancer treatment.

It's true 😂

If you're headed to the #AACRai25 plenary session on ML/AI for radiological imaging, check out speaker Caroline Chung's Cancer Research Landmarks commentary, Reproducibility and Reach of Radiomics, published as part of Cancer Research's special series: brnw.ch/21wU5XI

Anne Carpenter discussed "Accelerating Oncology Drug Discovery with the Power of Microscopy and AI" in a keynote lecture this morning during the AACR Special Conference on Artificial Intelligence and Machine Learning. #AACRai25 Anne Carpenter, PhD

Machine Learning and AI for Radiological Imaging: Catherine Coolens and Caroline Chung discussed this topic in a plenary session at the AACR Special Conference on Artificial Intelligence and Machine Learning. #AACRai25 Caroline Chung, MD

How Do We Make AI Research Better for Society? Jeff Leek and Casey Greene joined #AACRai25 cochair Marzyeh Ghassemi to address this question in a plenary at the AACR Conference on Artificial Intelligence and Machine Learning. #AACRai25 Marzyeh Casey Greene

Cancer Research aims to be a central platform that acknowledges the unique contributions of the data sciences to cancer research. Read the editorial by Editor-in-Chief Christine A. Iacobuzio-Donahue to learn how the journal is achieving this goal: brnw.ch/21wU69e

#AACRai25 cochairs Valentina Boeva and Benjamin Haibe-Kains adjourned the AACR Conference on Artificial Intelligence and Machine Learning. We thank all of the chairs—including Marzyeh and Bo Wang—for developing an outstanding program. Valentina Boeva Benjamin Haibe-Kains

AACR Marzyeh Bo Wang Valentina Boeva Benjamin Haibe-Kains Congrats to Valentina Boeva Benjamin Haibe-Kains Bo Wang Marzyeh on such successful #AACRai25 thanks to inspiring speakers & session chairs Anne Carpenter, PhD @Fertiglab …What a surprise poster award to our lab heroes Josh Squires and Andrew Hoffmann Northwestern Feinberg School of Medicine Lurie Cancer Center Chan Zuckerberg Initiative

🔥Just wrapped up an incredible three days in Montreal at the AACR (AACR ) Special Conference on Artificial Intelligence and Machine Learning — the first AACR event fully dedicated to exploring how AI is reshaping cancer research and care. I was deeply honored to serve as one of

Dr. Robert Winn recognized that improving care for cancer patients means bringing translational research into all communities. Read how Dr. Rob Winn is a driving force against cancer in Leading Discoveries: brnw.ch/21wU6jv

Goodbye Montreal! The special #AACR conference on AI and ML in Cancer Research was a fantastic event! Hope it’s not the last time we organize it! #AACRai25 Benjamin Haibe-Kains

This is creator of VLC media player . He refused tens of millions of dollars just to keep VLC ads-free , meet Jean-Baptiste Kempf.

I agree. Do you?

Trained on 2M+ interaction complexes, ATOMICA learns atomic-to-molecular embeddings of interaction interfaces Ada Fang In the latest preprint: 🎯 Wetlab tests of AI predictions: Experimental validation confirms heme binding for 5 ATOMICA-predicted sites in uncharacterized

🚀 Excited to share our latest protocol in Nature Protocols : "scGPT: End-to-end Protocol for Fine-tuned Retinal Cell Type Annotation"! Single-cell RNA-seq is transforming biology, but annotating large-scale, high-resolution data is challenging. Our team introduces a powerful

#TeamUHN showed up at the AACR Special Conference in Cancer Research! 🙌 Check out highlights from the Cancer Digital Intelligence team ⬇️

The use of machine learning models to predict PFS and OS outcomes from waterfall plots in RCTs (MAP-OUTCOMES) in ESMO Open. ML tool using depth of response with non-cytotoxic therapies predicting survival, potentially supporting go-no-go decisions. esmoopen.com/article/S2059-…