{"id":87,"date":"2017-10-24T16:04:50","date_gmt":"2017-10-24T16:04:50","guid":{"rendered":"http:\/\/labs.icahn.mssm.edu\/samuelcholab\/?page_id=87"},"modified":"2019-09-26T14:14:36","modified_gmt":"2019-09-26T14:14:36","slug":"bigdata","status":"publish","type":"page","link":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/bigdata\/","title":{"rendered":"Big Data Research"},"content":{"rendered":"<p>The Cho spine lab\u2019s 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 <a href=\"https:\/\/www.facs.org\/quality-programs\/acs-nsqip\">National Quality Improvement Project (NSQIP)<\/a> administered by the American College of Surgeons, <a href=\"https:\/\/www.hcup-us.ahrq.gov\/nrdoverview.jsp\">National Readmission Data (NRD)<\/a>, <a href=\"https:\/\/www.hcup-us.ahrq.gov\/nisoverview.jsp\">National Inpatient Sample (NIS)<\/a>, and <a href=\"https:\/\/www.hcup-us.ahrq.gov\/kidoverview.jsp\">Kids\u2019 Inpatient Database<\/a>. 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 <a href=\"https:\/\/www.nvidia.com\/en-us\/data-center\/dgx-1\/\">Nvidia\u2019s DGX-1<\/a>, 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.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Cho spine lab\u2019s 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 [&hellip;]<\/p>\n","protected":false},"author":86,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"class_list":["post-87","page","type-page","status-publish","hentry"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/pages\/87","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/users\/86"}],"replies":[{"embeddable":true,"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/comments?post=87"}],"version-history":[{"count":5,"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/pages\/87\/revisions"}],"predecessor-version":[{"id":343,"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/pages\/87\/revisions\/343"}],"wp:attachment":[{"href":"https:\/\/labs.icahn.mssm.edu\/samuelcholab\/wp-json\/wp\/v2\/media?parent=87"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}