4/ That is a challenge our partners at NeuroKids have been working to solve for years by supporting locally led surgical teams with training, mentorship, equipment, and stronger systems of care.

3/ 🌍 Across Africa, roughly 1,974 neurosurgeons serve 1.3B people. The expertise to treat conditions like hydrocephalus exists. The challenge is making sure that expertise can reach the children who need it.

2/ 🩺 Onore was born with hydrocephalus, a treatable condition that can lead to severe disability or death without timely care. His story is deeply personal, but the barriers his family faced in accessing treatment are shared by families around the world.

1/ 🌿 For Aisha and Stephano, learning that their newborn son Onore needed surgery was only the beginning of the journey to get him the care he needed.

6/ Every surgical video contains info about technique, decisions, anatomy, instruments, actions, and outcomes. Bringing more of that information together across surgeons, institutions, procedures, and geographies gives researchers the opportunity to build AI on a much broader picture of surgery.

5/ 🌟 We were also joined by X.Y. Han and Dr. Kee B. Park, who helped us widen the conversation beyond what's possible today and the challenges we still need to solve to move surgical data science forward.

4/ 🩺 The goal is bigger than recognizing what happens in an operation. It’s understanding the patterns of surgery well enough to better quantify surgical processes and decision-making, and evaluating how specialized surgical models compare with today’s frontier AI models.

3/ Our Founder, Daniel Donoho, opened with the clinical motivation behind SDSC’s work and why understanding the context of surgery matters. Our CTO Neeraj Mainkar, and Senior ML Engineer Jack Cook provided an in-depth look at how we’re teaching AI to identify patterns in surgical video.

2/ 💡 The evening sparked a lot of thoughtful discussion about where surgical AI is today, and what it will take to move the field forward. One thing is clear: better surgical AI starts with better surgical data.

1/ 🗣️ Last week, we brought together surgeons, computer scientists, and researchers in NY to discuss a deceptively difficult question: how do we know when AI actually understands surgery?

2/ 🩺 In surgery, that means turning what happens in the operating room into surgeon feedback, enabling them to learn from thousands of procedures beyond those they personally witness, and making specialist knowledge available far beyond the hospitals where it originates.

1/ 🌟 The future of AI in healthcare doesn’t have to be a choice between humans and machines. In a letter published in The Telegraph, SDSC Founder Dr. Daniel Donoho makes the case for a different vision of AI in healthcare: “AI should develop human expertise, not replace it.”