Webinar: Biostatistics and Bioinformatics Seminar – ‘Machine Learning in Biomedical and Health Sciences’
January 27, 12:00 pm to 1:00 pm
Presented by: Vasant G Honavar, PhD, Dorothy Foehr Huck and J. Lloyd Huck Chair in Biomedical Data Sciences and Artificial Intelligence; Professor, Informatics, Computer Science, Bioinformatics and Genomics, Neuroscience, and Public Health Sciences; Professor, Data Sciences Undergraduate Program
About the presentation: The unprecedented advances in our ability to acquire and process diverse types of data, and the resulting emergence of “big data” offers unprecedented opportunities for accelerating discoveries in biomedical and health sciences. They also drive fundamental methodological advances in artificial intelligence in general, and machine learning and causal inference in particular. I will describe several examples, drawn from research in my lab, of successful applications of artificial intelligence yielding in new tools for biomedical research, e.g., for characterizing and predicting bimolecular interactions and complexes, identifying metagenomic biomarkers of inflammatory bowel disease, elucidating brain activity biomarkers of age-related cognitive declines, and predicting cancer survival. I will provide some examples of methodological advances in machine learning, e.g., federated machine learning algorithms for settings where access constraints prevent centralized access to data, algorithms for predictive modeling from ultra-high dimensional, ultra-sparse, irregularly sampled, longitudinal data for predicting health risks from longitudinal clinical records. I will conclude with a brief discussion of some open problems.
To join via Zoom, visit https://pshealth.zoom.us/j/94860982030
To join via phone, dial 929-205-6099.
Meeting ID: 948 6098 2030
Passcode to enter seminar: 320367