Congratulations to Serena Yeung-Levy, Alejandro Lozano, Minwoo Sun, Jeff Nirschl, and James Burguess on receiving an NVIDIA Academic Grant in support of BioMed-MLLM: A Family of Open Multi-modal Large Language Models for Biomedicine.
The project began this April and will complete in September, 2025.
Tumor boards are “high-stakes, high-cost meetings for high-risk patients,” says Timothy Keyes, a data scientist at Stanford Health Care and a combined MD and PhD candidate in cancer biology and biomedical informatics at Stanford University School of Medicine.
Read the story here: https://news.microsoft.com/source/features/ai/meet-4-developers-leading-the-way-with-ai-agents/
| Dr. Roxana Daneshjou, Laura Adams, and Vardit Ravitsky, all experts at the intersection of healthcare, ethics, and technology, join host Peter Lee to discuss the responsible implementation of AI in healthcare. Daneshjou, a Stanford physician-scientist bridging dermatology, biomedical data science, and AI, discusses her work on identifying, understanding, and mitigating bias in AI systems and also leveraging AI to better serve patient needs.
Listen here: https://www.microsoft.com/en-us/research/podcast/laws-norms-and-ethics-for-ai-in-health/ |
The DBDS Education Committee undertook a “Curriculum Review Project” that culminated in a published review about graduate curriculum in Biomedical Data Science. Read it ahead of print here: https://www.annualreviews.org/content/journals/10.1146/annurev-biodatasci-090624-022951. The full publication will be available in August. Authors: Christine Y. Yeh, Dennis P. Wall, Karen Matthys, Chiara Sabatti, and Julia A. Palacios.