32 citations · 42 across the 16 of their papers we have counts for
10 papers · 1 filter
DynamicDx: Evaluating Evidence Acquisition in Video-Based Diagnosis
Jiahui Li, Yutong Guo, Nan Yang +3
Diagnosing a patient from video requires more than recognizing the sign: a vision-language model must turn what it sees into hypotheses, questions and tests. DynamicDx evaluates ea…
Physics-Constrained Deep Learning Model for Contactless Blood Pressure Monitoring from Triaxial Bodyseismography
Yuanyuan Zhang, Yida Zhang, Jiahui Li +6
Ballistocardiography (BCG) is promising for unobtrusive long-term blood pressure (BP) monitoring in laboratory settings, but traditional BCG signals are vulnerable to the variation…
EarlyDx: An Admission-Anchored Benchmark for Open-Ended Generation of Evidence-Supported ED-Encounter Diagnoses
Jiahui Li, Ruili Fang, Zishuai Liu +5
Clinical diagnosis at hospital admission must be made rapidly from limited, incomplete evidence. Existing diagnosis-prediction benchmarks are poorly suited to this setting: they re…
LastAct: Trajectory-Guided Latest-Activity Localization for Real-Time Smart-Home Activity Recognition
Zishuai Liu, Ruili Fang, Jin Lu +1
Human Activity Recognition (HAR) from ambient sensors enables smart-home applications such as health monitoring and assisted living. In realistic deployments, however, sensor event…
Peak-Detector: Explainable Peak Detection via Instruction-Tuned Large Language Models in Physiological Sign
Jiahui Li, Yida Zhang, Zixuan Zeng +10
Accurate peak detection across diverse cardiac physiological signals, including the Electrocardiogram (ECG), Photoplethysmogram (PPG), Ballistocardiogram (BCG), and Bodyseismograph…
DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition
Jiahui Li, Ruili Fang, Zishuai Liu +3
Beat-level Electrocardiography (ECG) arrhythmia detection aims to assign an arrhythmia class to each beat in a recording, yet many existing systems treat beats as isolated local in…
Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods
Taida Li, Yujun Yan, Fei Dou +2
Deep learning for cross-subject EEG decoding is hindered by high inter-subject variability, which introduces a severe domain shift between training and unseen test subjects. This s…
SIGMA: Semantic Identifier Grouping for Molecular Autoregression
Xinyu Wang, Fei Dou, Jinbo Bi +1
Autoregressive molecular models assign probability to molecular serializations even though chemical identity is invariant to serialization. Equivalent serializations can therefore…
LARV: Data-Free Layer-wise Adaptive Rescaling Veneer for Model Merging
Xinyu Wang, Ke Deng, Fei Dou +2
Model merging aims to combine multiple fine-tuned models into a single multi-task model without access to training data. Existing task-vector merging methods such as TIES, TSV-M, a…
Achieving Fine-grained Cross-modal Understanding through Brain-inspired Hierarchical Representation Learning
Weihang You, Hanqi Jiang, Yi Pan +3
Understanding neural responses to visual stimuli remains challenging due to the inherent complexity of brain representations and the modality gap between neural data and visual inp…