Professor Noémie Elhadad is an Associate Professor of Biomedical Informatics, affiliated with Computer Science at Columbia University. Her research is at the intersection of machine learning, technology, and medicine. She investigates ways to support clinicians, patients, and health researchers in their information workflow by automatically extracting and making accessible information from unstructured, large, often messy data.
- Amy P. Abernethy, US FDA
- Graeme Archer, GSK R&D
- Jesse Berlin, Johnson & Johnson
- Lawrence Carin, Duke
- Noémie Elhadad, Columbia
- Igor Jurisica, Krembil Research Institute and University of Toronto
- Faisal Khan, AstraZeneca
- Kannan Natarajan, Pfizer
- Amol Navathe, University of Pennsylvania
- Adler Perotte, Columbia
- Patrick Ryan, Janssen Research and Development
- Mary Ann Slack, US Food and Drug Administration (FDA)
- Simon Tavaré, Columbia
- Mihaela van der Schaar, Cambridge
- Li Wang, AbbVie
Countdown to AIPM
AIPM has begun!
Welcome Address — David Madigan, Ph.D., Columbia University
A Perspective on the Promise and Pitfalls of Artificial Intelligence in Clinical Drug Development — Kannan Natarajan, Pfizer Inc.
Machine Learning: Changing the future of healthcare – from next generation clinical trials to individualized treatment effects — Mihaela van der Schaar, University of Cambridge
Discussant — Patrick Ryan, Janssen Research and Development
ML and AI in Clinical Development and Statistical Innovation — Wang Li, AbbVie.
Opportunities for AI in Healthcare — Lawrence Carin, Duke University
- Demissie Alemayehu, Pfizer Inc.
- David Madigan, Columbia University