collaborators

8 papers

cs.LG2026

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…

q-bio.GN2025

Integrating Epigenetic and Phenotypic Features for Biological Age Estimation in Cancer Patients via Multimodal Learning

Shuyue Jiang, Wenjing Ma, Shaojun Yu +3

Biological age, which may be older or younger than chronological age due to factors such as genetic predisposition, environmental exposures, serves as a meaningful biomarker of agi…

cs.LG2025

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…

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…

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…