6 papers · 1 filter
Neural Signals Generate Clinical Notes in the Wild
Jathurshan Pradeepkumar, Zheng Chen, Jimeng Sun
Generating clinical reports that summarize abnormal patterns, diagnostic findings, and clinical interpretations from long-term EEG recordings remains labor-intensive. We present CE…
Tokenizing Single-Channel EEG with Time-Frequency Motif Learning
Jathurshan Pradeepkumar, Xihao Piao, Zheng Chen +1
Foundation models are reshaping EEG analysis, yet an important problem of EEG tokenization remains a challenge. This paper presents TFM-Tokenizer, a novel tokenization framework th…
ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation
Rikuto Kotoge, Ziwei Yang, Zheng Chen +4
Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging task and often requires downstream anal…
Long-Term EEG Partitioning for Seizure Onset Detection
Zheng Chen, Yasuko Matsubara, Yasushi Sakurai +1
Deep learning models have recently shown great success in classifying epileptic patients using EEG recordings. Unfortunately, classification-based methods lack a sound mechanism to…
GeSubNet: Gene Interaction Inference for Disease Subtype Network Generation
Ziwei Yang, Zheng Chen, Xin Liu +5
Retrieving gene functional networks from knowledge databases presents a challenge due to the mismatch between disease networks and subtype-specific variations. Current solutions, i…
Towards Physiologically Sensible Predictions via the Rule-based Reinforcement Learning Layer
Lingwei Zhu, Zheng Chen, Yukie Nagai +1
This paper adds to the growing literature of reinforcement learning (RL) for healthcare by proposing a novel paradigm: augmenting any predictor with Rule-based RL Layer (RRLL) that…