ArXiv Preprint
A collection of the extended abstracts that were presented at the 2nd Machine
Learning for Health symposium (ML4H 2022), which was held both virtually and in
person on November 28, 2022, in New Orleans, Louisiana, USA. Machine Learning
for Health (ML4H) is a longstanding venue for research into machine learning
for health, including both theoretical works and applied works. ML4H 2022
featured two submission tracks: a proceedings track, which encompassed
full-length submissions of technically mature and rigorous work, and an
extended abstract track, which would accept less mature, but innovative
research for discussion. All the manuscripts submitted to ML4H Symposium
underwent a double-blind peer-review process. Extended abstracts included in
this collection describe innovative machine learning research focused on
relevant problems in health and biomedicine.
Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy
2022-11-28
