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Ada Lovelace Computational Health Lecture Series

Ada Lovelace Day, held every year on the second Tuesday of October, was created to celebrate one of the first woman computer programmers. It is an international celebration of the achievements of women in science, technology, engineering and mathematics (STEM). It aims to increase the roles of women within the STEM sectors and support women already working in STEM.

In 2020, the National Library of Medicine (NLM) launched its Ada Lovelace Day Lecture to recognize the contributions of computer scientists in research on health and biomedicine. The annual lecture is sponsored by the NLM Intramural Research Program.

Human-centered AI Approaches for Individualized Self-management Regimens

Event Date: Tuesday, October 11, 2022

Time: 3:00 - 4:00 PM ET

Speaker: Noémie Elhadad, PhD

View on NIH Videocast

Presentation Description:

Personal health informatics solutions have been proposed to support self-management, to scaffold problem solving for individuals, and to promote experimentation that help identify potential triggers of disease flares across a range of health conditions. In many chronic diseases however, there is strong evidence of person-to-person variation in treatment responses and associated symptoms. In addition, there are often no predetermined policy guidelines for self-management, and if there are, individuals are left with the burden of translating them into their day-to-day lives. In this talk, I will discuss the challenges and exciting research directions for augmenting personal health informatics systems with AI-driven recommendations for self-management strategies. Because self-management is more successful when aligned with an individual's goals and context of daily living, as well as with their own health status and physiological responses, I argue that the promise of automated recommendations hinges on their personalization and posit that reinforcement learning is a promising technique for learning and delivering such personalized self-management recommendations, if designed in a human-centered fashion.

Speaker Bio:

Noémie Elhadad, PhD is an Associate Professor of Biomedical Informatics, affiliated with Computer Science and the Data Science Institute at Columbia University. She serves as Vice Chair for Research and Graduate Program Director for the Department of Biomedical Informatics (DBMI). She leads Even, the Data-Powered Women's Health Research Initiative at Columbia University as well as the Citizen Endo project, which advances research in endometriosis through citizen science. Dr. Elhadad’s research interests are at the intersection of machine learning, natural language processing, medicine, and technology. She investigates ways in which observational clinical data (e.g., electronic health records) and patient-generated data (e.g., online health community discussions, mobile health data) can enhance access to relevant information for clinicians, patients, and health researchers alike and can ultimately impact healthcare and health of patients.

Prior to joining Columbia DBMI in 2007, Dr. Elhadad completed her PhD in Computer Science at Columbia University and was an Assistant Professor in Computer Science at The City University of New York.

How to Join: 

This talk will be broadcast live and archived through the NIH Videocast website.

Interpreting services are available upon request. Individuals with disabilities who need reasonable accommodation to participate in this lecture should contact Ms. Queenmoore Okeke at or the Federal Relay (1-800-877-8339).

Questions during the presentation can be sent to:

Sponsored by:

Valerie Florance, PhD
Acting Scientific Director for Intramural Research Program, National Library of Medicine

View past lectures