The Cho spine lab’s team comprises of faculty, fellows, residents and medical/graduate students of Mount Sinai with a diverse background. Prior to joining the lab, some have worked as consultants, machine learning engineers and data scientists. Our lab seeks to leverage big data and utilize a wide array of computer vision, natural language processing, and reinforcement learning techniques. Many projects are currently underway using national databases such as the National Quality Improvement Project (NSQIP) administered by the American College of Surgeons, National Readmission Data (NRD), National Inpatient Sample (NIS), and Kids’ Inpatient Database. In addition, we have created a Mongo database in-house that covers over 7 million patient encounters at the Mount Sinai Health System hospitals and facilities, which amount to over 1 terabyte of data. The lab maintains significant computing, both CPUs and GPUs, including Nvidia’s DGX-1, to support our work. Given our unique background and expertise as both MDs and machine learners with access to immense clinical data and sufficient computing, we are poised to change the way in which medicine is practiced in the near future.
Interview with Samuel Cho, MD
- Global Spine Congress 2019
- NASS 2018 Robotics and Navigation Best Paper Award
- 2018 Match Day
- Kuwaiti Ministry of Health Visit
- Global Spine Journal – Best Papers of 2017!
- NASS 2017!
- Graduation with Distinction in Research Achievement Ceremony – Icahn School of Medicine at Mount Sinai
- Global Spine Journal – Best Paper 2016