Navigating the Digital Health Landscapes: Unraveling Complex Illnesses by Understanding the Trajectories of the Patients

One of the major challenges in the post-genomic era is deciphering the complexity of diseases such as mental and physical health, which is complicated by the variability of clinical symptoms and the persistent uncertainty due to inconsistent replication of biological findings associated with these symptoms. This talk addresses the complexity of disease progression in both mental and physical health, hindered by variability in symptoms and inconsistent replication of findings. We explore digital health solutions, using multi-omics profiling (genetics, epigenetics, transcriptomics, etc.) and multimodal neuroimaging (MRI, EEG, DBS) to personalize treatments. Integrating AI and ML enables the identification of unique disease pathways, guiding effective, individualized care. Key findings include insights into schizophrenia’s diversity, genetic-environment interactions in personality, cognitive decline risk in COVID-19 patients, and prognostic biomarkers in cancers and cardiometabolic diseases, with telemedicine innovations poised to significantly reduce readmission rates.

Igor (Jorge) Sergio Zwir, Ph.D. Associate Professor (Tenure-track) Department of Psychiatry, Washington University School of Medicine Institute of Neuroscience, University of Texas Rio Grande Valley Department of Computer Science and AI, University of Granada, Spain (Tenured)

Please RSVP by November 4.

This session is part of the Dr. Herbert and Nicole Wertheim Leadership in Healthcare and Medicine Lecture Series.