collaborators

7 papers

cs.LG2025

FairTune: A Bias-Aware Fine-Tuning Framework Towards Fair Heart Rate Prediction from PPG

Lovely Yeswanth Panchumarthi, Saurabh Kataria, Yi Wu +3

Foundation models pretrained on physiological data such as photoplethysmography (PPG) signals are increasingly used to improve heart rate (HR) prediction across diverse settings. F…

cs.LG2025

Towards Synthesizing Normative Data for Cognitive Assessments Using Generative Multimodal Large Language Models

Victoria Yan, Honor Chotkowski, Fengran Wang +6

Cognitive assessments require normative data as essential benchmarks for evaluating individual performance. Hence, developing new cognitive tests based on novel image stimuli is ch…

cs.LG2025

Learning ECG Representations via Poly-Window Contrastive Learning

Yi Yuan, Joseph Van Duyn, Runze Yan +7

Electrocardiogram (ECG) analysis is foundational for cardiovascular disease diagnosis, yet the performance of deep learning models is often constrained by limited access to annotat…

cs.LG2025

Longitudinal Progression Prediction of Alzheimer's Disease with Tabular Foundation Model

Yilang Ding, Jiawen Ren, Jiaying Lu +4

Alzheimer's disease is a progressive neurodegenerative disorder that remains challenging to predict due to its multifactorial etiology and the complexity of multimodal clinical dat…

eess.IV2025

State-of-the-Art Stroke Lesion Segmentation at 1/1000th of Parameters

Alex Fedorov, Yutong Bu, Xiao Hu +2

Efficient and accurate whole-brain lesion segmentation remains a challenge in medical image analysis. In this work, we revisit MeshNet, a parameter-efficient segmentation model, an…

eess.SP2025

Fusion of ECG Foundation Model Embeddings to Improve Early Detection of Acute Coronary Syndromes

Zeyuan Meng, Lovely Yeswanth Panchumarthi, Saurabh Kataria +4

Acute Coronary Syndrome (ACS) is a life-threatening cardiovascular condition where early and accurate diagnosis is critical for effective treatment and improved patient outcomes. T…