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An Electrocardiogram Multi-task Benchmark with Comprehensive Evaluations and Insightful Findings
Yuhao Xu, Jiaying Lu, Sirui Ding +3
In the process of patient diagnosis, non-invasive measurements are widely used due to their low risks and quick results. Electrocardiogram (ECG), as a non-invasive method to collec…
EnECG: Efficient Ensemble Learning for Electrocardiogram Multi-task Foundation Model
Yuhao Xu, Xiaoda Wang, Jiaying Lu +6
Electrocardiogram (ECG) analysis plays a vital role in the early detection, monitoring, and management of various cardiovascular conditions. While existing models have achieved not…
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…
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…
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…
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…