1 citations · 1 across the 4 of their papers we have counts for
7 papers
Wavelet-Driven Masked Multiscale Reconstruction for PPG Foundation Models
Megha Thukral, Cyrus Tanade, Simon A. Lee +10
Wearable foundation models have the potential to transform digital health by learning transferable representations from large-scale biosignals collected in everyday settings. While…
Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025
Emily Alsentzer, Marie-Laure Charpignon, Bill Chen +90
The 6th Annual Conference on Health, Inference, and Learning (CHIL 2025), hosted by the Association for Health Learning and Inference (AHLI), was held in person on June 25-27, 2025…
HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series
Simon A. Lee, Cyrus Tanade, Hao Zhou +13
Wearable sensors provide abundant physiological time series, yet the principles governing their predictive utility remain unclear. We hypothesize that temporal resolution is a fund…
Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
Ulzee An, Moonseong Jeong, Simon A. Lee +3
Current challenges in developing foundational models for volumetric imaging data, such as magnetic resonance imaging (MRI), stem from the computational complexity of training state…
A Case Study Exploring the Current Landscape of Synthetic Medical Record Generation with Commercial LLMs
Yihan Lin, Zhirong Bella Yu, Simon Lee
Synthetic Electronic Health Records (EHRs) offer a valuable opportunity to create privacy preserving and harmonized structured data, supporting numerous applications in healthcare.…
Clinical ModernBERT: An efficient and long context encoder for biomedical text
Simon A. Lee, Anthony Wu, Jeffrey N. Chiang
We introduce Clinical ModernBERT, a transformer based encoder pretrained on large scale biomedical literature, clinical notes, and medical ontologies, incorporating PubMed abstract…