1 code implementation • 9 Mar 2024 • Samuel Schmidgall, Ji Woong Kim, Jeffrey Jopling, Axel Krieger
The absence of openly accessible data and specialized foundation models is a major barrier for computational research in surgery.
1 code implementation • 12 Feb 2024 • Samuel Schmidgall, Carl Harris, Ime Essien, Daniel Olshvang, Tawsifur Rahman, Ji Woong Kim, Rojin Ziaei, Jason Eshraghian, Peter Abadir, Rama Chellappa
There is increasing interest in the application large language models (LLMs) to the medical field, in part because of their impressive performance on medical exam questions.
no code implementations • 1 Jan 2024 • Samuel Schmidgall, Ji Woong Kim, Alan Kuntz, Ahmed Ezzat Ghazi, Axel Krieger
The dominant paradigm for end-to-end robot learning focuses on optimizing task-specific objectives that solve a single robotic problem such as picking up an object or reaching a target position.
no code implementations • 16 Nov 2020 • Ji Woong Kim, Changyan He, Muller Urias, Peter Gehlbach, Gregory D. Hager, Iulian Iordachita, Marin Kobilarov
We show that the network can reliably navigate a needle surgical tool to various desired locations within 137 microns accuracy in physical experiments and 94 microns in simulation on average, and generalizes well to unseen situations such as in the presence of auxiliary surgical tools, variable eye backgrounds, and brightness conditions.