AIMI Grand Rounds: AI-based Integration of Omics and EMR Data - Nima Aghaeepour, PhD

The AIMI Grand Rounds, sponsored by the Center for Artificial Intelligence in Medicine and Imaging (AIMI), is a virtual series held on every fourth Tuesday. The series is a crucial initiative for disseminating the latest AI advancements in medicine, aiming to drive transformative innovations in healthcare. Stanford participants of the live event can claim 1.0 CME credits: AMA PRA Category 1 Credits ™ or Non-Physician Participation Credit.

Speaker:

Nima Aghaeepour, PhD: The Anesthesiology, Perioperative, and Pain Medicine Endowed Professor, Stanford University 

Bio: Nima Aghaeepour is the Anesthesiology, Perioperative and Pain Medicine II Endowed Professor and Vice Chair for Research (data science) at Stanford University. His laboratory develops machine learning and artificial intelligence methods to study clinical and biological modalities in translational settings.  He is primarily interested in leveraging multiomics studies, wearable devices, and electronic health records to address clinical challenges.

Abstract: AI offers a powerful new lens to bridge the longstanding divide between biology and medicine, and between maternal and child health. Pregnancy and early life are shaped by dynamic, interconnected biological processes and complex clinical environments—yet data across these domains have traditionally remained siloed. In this presentation, I will describe our work developing AI systems that integrate multi-omics, wearable data, and electronic health records to model and modulate pregnancy and neonatal outcomes. These include foundation models that connect clinical and biological data modalities, as well as AI-driven strategies to personalize neonatal nutrition with an emphasis on long-term health. By unifying biological insights with clinical decision-making, we aim to advance a precision medicine paradigm for mothers and their children.