MIT Critical Data

Empowering research in critical care.

Transforming Critical Care

In many areas of science, government and business, data has become a major driver of innovation and success. We see the opportunity for the same revolution in critical care.

Meaningful use

Large amounts of data originating from critical care needs to be de-identified, analyzed and curated for it to be mined effectively. Clinicians and Data scientists must work together to understand and explore the meaningful, secondary use of Critical Care data.

Changing healthcare

Our vision is for the development of a care system consisting of Clinical Informatics without walls, in which the creation of evidence and clinical decision support tools is initiated, updated, honed and enhanced by scaling the access and meaningful use of clinical Data.

Partners

The latest from MIT Critical Data

2019.HST.953: Collaborative Data Science in Medicine

on August 6, 2019

HST.953: Collaborative Data Science in Medicine is a guide for students who are interested in performing retrospective research using data from electronic health records (Medical Information Mart for Intensive Care [MIMIC] database and eICU Collaborative Research Database [eICU-CRD]). The course covers steps of parsing a clinical question into a study design and methodology for data analysis and interpretation, with emphasis on the data curation process that is required before any analysis can be performed.

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2018.HST.953: Collaborative Data Science in Medicine

on July 24, 2018

Registration is Now Closed Please contact course faculty if you have any questions. 2018.HST.953: Collaborative Data Science in Medicine HST.953: Collaborative Data Science in Medicine is a course that focuses on the secondary analysis of clinical data that is routinely collected in the process of care. In this fall course, students will work with Boston-area clinicians on research projects with the goal of a publication-ready manuscript at the end of the semester.

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2017.HST.953: Collaborative Data Science in Medicine

on September 8, 2017

2017.HST.953: COLLABORATIVE DATA SCIENCE IN MEDICINE HST.953: Collaborative Data Science in Medicine, focuses on the secondary analysis of clinical data that is routinely collected in the process of care. In this course, students will work with Boston-area clinicians on research projects with the goal of a publication-ready manuscript at the end of the semester. Three of the 15 papers from last fall are already being reviewed by various clinical journals, while the rest are on track for submission over the next few months.

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Critical Datathon 2015

on September 25, 2015

Datathon 2015 This weekend long (September 25-27) event brings together clinicians, data scientists and innovators in healthcare to address current problems in intensive care. The increasing wealth of patient data available through electronic health records has created a surge in research funding and industry interest in health data analytics. Challenges in extracting knowledge from health record databases, however, are significant. The event will strengthen cross-disciplinary collaboration around secondary analysis of electronic health record data, helping to pave the way for reliable knowledge to be translated into action, for the benefit of patients.

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