Speaker Profile

Ph.D., Associate Professor, Stanford University

Biography
Nima Aghaeepour is an Associate Professor 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 global health challenges. His work is recognized by awards from numerous national and international organizations including the Bill and Melinda Gates Foundation, the March of Dimes Foundation, the Burroughs Wellcome Fund, the National Institute of General Medical Sciences, and the National Center for Advancing Translational Sciences.

Talk
An AI-Driven Taxonomy for Prematurity
Despite significant investments, preterm birth has remained the single largest cause of death in children under 5 years of age. I will discuss a series of studies using state-of-the-art biological profiling, electronic health records, and artificial intelligence techniques which aim to enable an integrated precision-medicine approach to predict, prevent, and manage preterm births.


 Session Abstract – PMWC 2023 Silicon Valley


Track 3, January 26

Track Co-Chairs:
Yoel Sadovsky, UPMC
Aleksandar Rajkovic, UCSF

Researchers have long been recognizing the uniqueness of women’s health and its substantial effect on clinical practice, acknowledging the increasing appreciation of the importance of multidisciplinary approaches to health and disease. In every organ system, there are diseases that are unique to women, more common in women than in men, or characterized by differences in disease course in women compared to men. This Track will focus on the following topics related to Women’s Health:

  • Chronic Diseases in Women
    - Marcia Stefanik, Stanford (Chronic Disease Prevention) - Linda Giudice, UCSF (Endometriosis)
  • Stem Cells, Preimplantation and Prenatal Genetics
    Chair: Akash Kumar, MyOme, Inc. (Ploygenic risk score)
    - Vitorio Sebastiano, Stanford (Stem cells and fertility)
    - Teresa Sparks, UCSF
    - Nathan Treff, Genomic Prediction
  • Precision Health for Mothers and Babies
    Chair: David Stevenson, U. of Stanford (Introduction: Towards Precision Health for Mothers and Babies)
    - Aleks Rajkovic, UCSF (Genomics of Pregnancy Loss)
    - Ivana Maric, Stanford (ML for Early Prediction)
    - Nima Aghaeepour, Stanford (AI-Driven Prematurity Taxonomy)
  • Components of Pregnancy Health
    Chair: Yoel Sadovsky, U. of Pittsburgh (Placental Health)
    - Marina Sirota, UCSF (Leveraging Molecular and Clinical Data)
  • Reproductive Aging (PANEL)
    Chair: Aleksandar Rajkovic, UCSF
    - Diana Laird, UCSF
    - Nikolina Lauc, GlycanAge
    - Dina Radenkovic, Gameto
  • Sex Differences
    - Noel Bairey Merz, Cedar Sinai (CV disease)
    - Danit Ariel, Stanford (Bone Health)