Surgical AI Trainer


AI feedback system to improve outcomes in surgery

Surgical AI Trainer evaluates surgeons' techniques using videos from real life surgeries, offering feedback to enhance patient outcomes. Unlike athletes, surgeons often lack performance evaluations due to the laborious nature of expert peer reviews. This feedback deficit can hinder skill advancement, potentially elevating patient risks. With the Surgical AI Trainer, surgeons simply upload their procedure video, the AI then assesses their performance, generating an interactive report. This pivotal tool empowers surgeons to pinpoint and rectify skill gaps, ultimately improving surgical results.


  • Dani Kiyasseh

    Dani Kiyasseh

    California Institute of Technology

    Dani operates at the intersection of artificial intelligence (AI) and healthcare. He is currently on the research faculty at Cedars-Sinai. He was a postdoctoral fellow at Caltech, jointly advised by Anima Anandkumar and Andrew Hung, where he developed AI systems to decode the activity of surgeons through videos. He completed his DPhil at the University of Oxford, under the guidance of David Clifton and Tingting Zhu, designing deep learning algorithms that overcome the challenges posed by limited labelled physiological time-series data, such as the electrocardiogram. He earned his BS in biomedical engineering from The Johns Hopkins University. Dani has broad interests in applied machine learning for healthcare, and focuses on developing resource-efficient and trustworthy clinical machine learning systems. He has spent time conducting machine learning research at Ford Motor Company, Mayo Clinic, Merck & Co., Flatiron Health, and Vicarious Surgical. His research has been published in ICML, NeurIPS, Nature Biomedical Engineering, and Nature Communications.more

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  • Andrew Hung

    Andrew Hung

    University of Southern California

    Dr. Hung is a surgeon scientist who specializes in robotic surgery for diseases of the kidney and prostate. His research interests include the development of artificial intelligence methods to improve surgeon skills assessment and training. Dr. Hung received his Bachelor of Science degree with honors from Yale University, and he completed his medical education at the Weill Medical College of Cornell University with honors in research. Dr. Hung completed his urology residency at the University of Southern California, and he stayed at USC for a fellowship in advanced laparoscopy and robotics. After spending 9 years on faculty at USC and attaining tenure, he joins the Department of Urology at Cedars-Sinai Medical Center in July 2023 as Vice Chair for Academic Development. Dr. Hung is internationally recognized as a leader in the development of innovative surgical simulation and assessment technologies. Supported by both industry grants and the National Institutes of Health, Dr. Hung has also become a leading innovator in the development of automated performance metrics for robotic surgery. His collaboration with data scientists at USC and Caltech has harnessed deep learning algorithms to better predict robotic surgical outcomes and automate surgeon skills assessment. more


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