*ABSTRACT*: Quality of life (QoL) is a crucial outcome and endpoint in research, clinical trials, and clinical practice, especially in noncommunicable chronic diseases. The QoL aims to provide valuable information for physicians and patients, potentially aiding in more accurate diagnosis and in identifying more effective treatments. Given the state of the personal technologies miniaturized in our smartphones and a variety of wearables, this outcome should have already been a standard of care. But is it? In this talk, I give an overview of the state of the art in digital endpoints of QoL, and present some recent examples of my own QoL modeling approaches that leverage deep learning, with insights from social and behavioral sciences. I emphasize the importance of mixed methods for designing and validating these models, especially prominent in the recent study of quantifying sexual health. I discuss the implications for personal technologies enabling accurate and timely digital endpoints of QoL.
*BIO*: Professor Katarzyna Wac, Ph.D., is a Full Professor of Information Science at the University of Geneva in Switzerland, where she leads the Quality of Life Technologies lab. She is also an Invited Professor of Health Informatics at the Department of Computer Science (DIKU) at the University of Copenhagen in Denmark. She has been affiliated with Stanford University and the Stanford Medical Centre since 2013. The QoL lab, established in 2010, aims to responsibly leverage daily life data sources to improve the quality of life of all individuals. The QoL lab's research interests include fundamental and algorithmic problems, as well as human-centric challenges related to the assessment and improvement of human behavior, health, and quality of life as they unfold naturally over time and in context. Her most recent research project focuses on the design of digital biomarkers of sexual health and is conducted in collaboration with Stanford University.
