Video Recording Available for Second +DS Fall Lunch and Learn Session

October 1, 2019

Full video of the second Fall 2019 Plus Data Science (+DS) Lunch and Learn session is now available online and can be accessed at the link below (Duke log-in required). The session, titled "A Window to the Brain: Analysis of Retinal Images with Deep Neural Networks" was presented on Tuesday, October 1 in the Learning Hall at the Trent Semans Center at Duke.

A Window to the Brain: Analysis of Retinal Images with Deep Neural Networks

Sharon Fekrat, MD, Professor of Ophthalmology; Associate Professor, Department of Surgery
Felipe Medeiros, MD, PhD, Joseph A.C. Wadsworth Professor of Ophthalmology

Dilraj Singh Grewal, MBBS, Associate Professor of Ophthalmology
Lawrence Carin, PhD; James L. Meriam Professor of Electrical and Computer Engineering; Vice President for Research, Duke University

Link to full video:

This event was part of the +DS Lunch and Learn series in fall 2019. +DS invites you to learn about how artificial intelligence (AI) is transforming healthcare through a series of lunch and learns this fall. Future topics to be presented later this fall include neural networks and retinal image analysis, machine learning approaches for autism screening, and natural language processing with communications between patients and clinicians. Detailed information for future events, including location and scheduling, is available here:

Both clinical and technical experts lead each session, with content split roughly 50/50 between the clinical setup and technical approach. Participants will learn about both the medical context and the applications of data science for health. The goal for these lunches is a fun, convenient way for the Duke community to learn about data science and engage with Duke’s data science for health community, including clinicians, quantitative experts, faculty, trainees, and students.

+DS is a Duke-wide program operating in partnership with departments, schools, and institutes to enable faculty, students, and staff to employ data science at a level tailored to their needs, level of expertise, and interests. To learn more, please visit