Link to the preprint discussed: https://arxiv.org/pdf/2505.10251

Link to the project with explanations: https://h-surgical-robot-transformer.github.io/

A surgical robot that corrects its own mistakes sounds like science fiction.

In this paper, new research from Johns Hopkins & Stanford makes it a reality. But is it ready for the operating room?

The new SRT-H system allows a da Vinci robot to autonomously perform key steps of a gallbladder removal, achieving a 100% success rate in a lab setting. It can even identify and correct its own errors in real-time—a huge leap for surgical AI.

But the biggest challenge isn't executing a perfect plan; it's managing the messy, unpredictable reality of a live patient.

In the latest episode of The Health AI Brief podcast, we break down:

- The gap between lab performance and clinical reality.

- The crucial shift from chasing full autonomy to proving ultra-reliable, supervised autonomy.

It's a really interesting and impressive application of AI. This isn't just about technology. It's about building trust, managing risk, and creating AI that surgeons can actually rely on.

Authors of the work: Ji Woong (Brian) Kim1,2, Juo-Tung Chen1, Pascal Hansen1, Lucy X. Shi2, Antony Goldenberg1, Samuel Schmidgall1, Paul Maria Scheikl1, Anton Deguet1, Brandon M. White1, De Ru Tsai3, Richard Cha3, Jeffrey Jopling1, Chelsea Finn2, Axel Krieger1

1 Johns Hopkins University, 2 Stanford University, 3 Optosurgical

#AIinHealthcare #SurgicalRobotics #AutonomousSurgery #HealthTech #DigitalHealth #MedTech #AIinSurgery #MachineLearning #daVinciSurgery #PatientSafety #FutureofMedicine #ClinicalInnovation #JohnsHopkins #Stanford

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