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Activity Number: 502 - Learning Beyond the Introductory Statistics Classroom
Type: Contributed
Date/Time: Thursday, August 6, 2020 : 10:00 AM to 2:00 PM
Sponsor: Section on Statistics and Data Science Education
Abstract #313067
Title: The Duke AI Health Data Science Fellowship Program: Training the Next Generation of Health Data Scientists Through Real World Experience
Author(s): Lisa Wruck* and Robert Overton and Silvana Lawvere and Ricardo Henao and David Page and Michael Pencina and Lawrence Carin
Companies: Duke Clinical Research Institute and Duke Clinical Research Institute and Duke Clinical Research Institute and Duke Departments of Electrical and Computer Engineering / Biostatistics and Bioinformatics and Duke Department of Biostatistics and Bioinformatics and Duke School of Medicine and Duke University
Keywords: data science; education; workforce development; training

The Duke AI Health Data Science Fellowship Program was launched in 2020 to train the next generation of health data scientists. Designed for candidates with an MS degree in a quantitative field and an interest in healthcare applications, the 2-year experience is a key component of Duke University’s strategic investment in data science as a tool for solving important problems in healthcare. This novel early career program incorporates an intensive but supportive curriculum in cutting-edge data science, engaging learners in impactful healthcare analytics projects with leading experts in their respective fields. Candidates are integrated into interdisciplinary teams comprising quantitative and clinical experts, operations personnel and students, and mentored by the team quantitative lead. Teams are embedded within clinical specialties (surgery, cardiology, palliative care) to develop domain knowledge and contribute to concrete applications incorporating risk prediction, image analysis and natural language processing. I will describe educational objectives, approach to incorporating the educational mission into impactful healthcare analytic projects, and metrics used to assess success.

Authors who are presenting talks have a * after their name.

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