collaborators

5 papers

cs.LG2025

Wav2Arrest 2.0: Long-Horizon Cardiac Arrest Prediction with Time-to-Event Modeling, Identity-Invariance, and Pseudo-Lab Alignment

Saurabh Kataria, Davood Fattahi, Minxiao Wang +5

High-frequency physiological waveform modality offers deep, real-time insights into patient status. Recently, physiological foundation models based on Photoplethysmography (PPG), s…

cs.AI2025

A Unified AI Approach for Continuous Monitoring of Human Health and Diseases from Intensive Care Unit to Home with Physiological Foundation Models (UNIPHY+)

Minxiao Wang, Saurabh Kataria, Juntong Ni +15

We present UNIPHY+, a unified physiological foundation model (physioFM) framework designed to enable continuous human health and diseases monitoring across care settings using ubiq…

cs.LG2025

Estimating Clinical Lab Test Result Trajectories from PPG using Physiological Foundation Model and Patient-Aware State Space Model -- a UNIPHY+ Approach

Minxiao Wang, Runze Yan, Carol Li +7

Clinical laboratory tests provide essential biochemical measurements for diagnosis and treatment, but are limited by intermittent and invasive sampling. In contrast, photoplethysmo…

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…

cs.LG2025

Continuous Cardiac Arrest Prediction in ICU using PPG Foundation Model

Saurabh Kataria, Ran Xiao, Timothy Ruchti +5

Non-invasive patient monitoring for tracking and predicting adverse acute health events is an emerging area of research. We pursue in-hospital cardiac arrest (IHCA) prediction usin…