Daniel Donoho, MD

Surgical Data Science Collective Verified account @SurgicalDSC · Oct 2

🌟 Are you a medical student or resident that is curious about the future of AI in surgery?

On Monday, October 5th at 2pm Eastern, SDSC is hosting an introductory session for those interested in surgical innovation, AI, research, and the growing role of surgical video in education and clinical care.

We’ll discuss:
🔹 What Surgical Data Science is and why it matters
🔹 How AI and surgical video are already being used in training and research
🔹 A walkthrough of SDSC’s free Surgical Video Platform
🔹 Opportunities for students and residents to get involved early through research, collaboration, and innovation initiatives

👉 You don’t need a technical background or prior AI experience to join. If you’re interested in where surgery is headed over the next decade, this session is for you.

📆 Monday, October 5th
⏰ 2:00 PM EST Introductory Zoom Session with the Surgical Data Science Collective (SDSC)
🔗 Video call link: meet.google.com/ihf-tfdx-sta
Feel free to share with your classmates, co-residents, and anyone interested in the intersection of surgery and emerging technology.

#surgicalvideo #datascience #research #AIinMedicine

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Surgical Data Science Collective Verified account @SurgicalDSC · Aug 18

🧠 Throughout #NeurosurgeryAwarenessMonth, we've been exploring how AI can help make aspects of neurosurgical care more measurable. Our next Data Science Roundtable brings that conversation into the neurocritical care setting.

📣 Join Dr. Rui Feng for a discussion on “Applications of AI pose estimation for neurological monitoring across NICU and NSICU: From concept to deployment”

🩺 Rui Feng, MD, MSc is a skull base surgery fellow at Thomas Jefferson University, following completion of her neurosurgery residency at the Icahn School of Medicine at Mount Sinai. She earned her undergraduate degree in Neuroscience and Psychology from the University of Toronto, a Master of Science in Clinical Neuroscience from University College London, and her medical degree from the Icahn School of Medicine at Mount Sinai.

Dr. Feng's clinical and research interests center on skull base surgery, neurocritical care, and the application of artificial intelligence to improve neurosurgical practice. As a Mount Sinai Health System TL1 Postdoctoral Scholar, an NIH-funded program supporting the next generation of clinician-scientists, she developed novel AI-based approaches for neurological assessment in the neurosurgical intensive care unit. Her research explored the use of computer vision and pose-tracking technology to enable more objective, continuous monitoring of neurological function, with the goal of improving patient care and clinical decision-making. 

Following her skull base fellowship, Dr. Feng will rejoin the faculty at Mount Sinai as a neurosurgery attending, where she will further advance her clinical research and academic initiatives.

📅 Wednesday, August 26, 2026
⏰ 12:00–1:00 PM Eastern
👉 Register: us06web.zoom.us/meeting/regist…

🗣️ Our Data Science Roundtables bring together clinicians, researchers, engineers, and others interested in advancing surgical and medical AI. Join the conversation, and if you're interested in collaborating with SDSC on surgical video, AI, or research, we'd love to hear from you.
🤝 Collaborate with SDSC: surgicalvideo.io/research

#Neurosurgery #NeurocriticalCare #MedicalAI #AIforGood

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Isaac Kohane Verified account @zakkohane · Jul 23

Two years ago I took two hundred pairs of simulated patients and did something boring: I decided, one pair at a time, which of two patients would be seen first. I asked state-of-the-art LLMs (@google @openai @AnthropicAI) to do the same with the same patients. I just repeated the experiment.

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Kirill Verified account @kskblv · Jun 10

We benchmarked Fable on surgical tool detection so you don’t have to. At almost 2 cents/image, Claude Fable 5 still loses to a compact image classifier. Will frontier VLMs ever catch up in surgical perception? Read our paper to learn more: arxiv.org/abs/2603.27341

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