50 citations · 59 across the 11 of their papers we have counts for
8 papers
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention
Adiba Orzikulova, Han Xiao, Zhipeng Li +7
Despite a rich history of investigating smartphone overuse intervention techniques, AI-based just-in-time adaptive intervention (JITAI) methods for overuse reduction are lacking. W…
Asymmetry in Low-Rank Adapters of Foundation Models
Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi +6
Parameter-efficient fine-tuning optimizes large, pre-trained foundation models by updating a subset of parameters; in this class, Low-Rank Adaptation (LoRA) is particularly effecti…
Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals
Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi
Heart failure is a debilitating condition that affects millions of people worldwide and has a significant impact on their quality of life and mortality rates. An objective assessme…
VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception
Jiyoung Lee, Seungho Kim, Seunghyun Won +6
AI alignment refers to models acting towards human-intended goals, preferences, or ethical principles. Given that most large-scale deep learning models act as black boxes and canno…
AI Models Close to your Chest: Robust Federated Learning Strategies for Multi-site CT
Edward H. Lee, Brendan Kelly, Emre Altinmakas +27
While it is well known that population differences from genetics, sex, race, and environmental factors contribute to disease, AI studies in medicine have largely focused on locoreg…