8 papers · 1 filter
A Comprehensive Inference-Time Augmentation Framework in Physiological Signals: Application to PPG-Based AF Detection
Davood Fattahi, Runze Yan, Saurabh Kataria +2
Objective: Accurate classification of physiological signals in real-world deployments is challenged by sensor noise, motion artifacts, and distribution shifts between training and…
Noninvasive Intracranial Pressure Estimation Using Subspace System Identification and Bespoke Machine Learning Algorithms: A Learning-to-Rank Approach
Anni Zhao, Ayca Ermis, Jeffrey Robert Vitt +10
Accurate noninvasive estimation of intracranial pressure (ICP) remains a major challenge in critical care. We developed a bespoke machine learning algorithm that integrates system…
Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signals
Saurabh Kataria, Yi Wu, Zhaoliang Chen +21
Foundation models are large-scale machine learning models that are pre-trained on massive amounts of data and can be adapted for various downstream tasks. They have been extensivel…
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…
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…
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…