The research area of AI for Health, Computational Biology, and Biomedical/Clinical Informatics is an interdisciplinary field focused on advancing healthcare and biological sciences through the use of artificial intelligence, computational methods, and informatics. AI for Health aims to improve patient care by developing predictive models, enhancing medical imaging, enabling personalized medicine, and accelerating drug discovery. It leverages machine learning and natural language processing to analyze complex medical data, offering more accurate diagnostics and treatment options.
Computational Biology focuses on understanding biological systems through computational models and simulations. This includes analyzing genetic and protein data, modeling biological processes, and developing bioinformatics tools to manage large-scale biological datasets. The goal is to gain insights into disease mechanisms, gene functions, and biological interactions, which can lead to innovations in areas like genomics, proteomics, and synthetic biology.
Biomedical/Clinical Informatics enhances healthcare by optimizing the use of data and knowledge in clinical settings. This includes developing electronic health records, clinical decision support systems, and health information exchanges to improve patient care and clinical workflows. Patient-centered informatics also plays a role in engaging patients through mobile health applications and digital tools, contributing to better health outcomes and more efficient healthcare delivery. The integration of these fields is crucial for advancing precision medicine and improving overall healthcare systems.
Faculty
Rajeev Alur
Yoseph Barash
Susan Davidson
James Gee
Sharath Guntuku
Zachary Ives
Kevin Johnson
Sampath Kannan
Juhnyong Kim
Konrad Kording
Qi Long
Mayur Naik
Joshua Plotkin
Dan Roth
Harvey Rubin
Val Tannen
Lyle Ungar
René Vidal
