1 citations · 1 across the 11 of their papers we have counts for
11 papers
ODEBrain: Continuous-Time EEG Graph for Modeling Dynamic Brain Networks
Haohui Jia, Zheng Chen, Lingwei Zhu +6
Modeling neural population dynamics is crucial for foundational neuroscientific research and various clinical applications. Conventional latent variable methods typically model con…
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…
DeepEvidence: Empowering Biomedical Discovery with Deep Knowledge Graph Research
Zifeng Wang, Zheng Chen, Ziwei Yang +5
Biomedical knowledge graphs (KGs) encode vast, heterogeneous information spanning literature, genes, pathways, drugs, diseases, and clinical trials, but leveraging them collectivel…
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…
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…
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…
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…
Can Large Language Models Replace Data Scientists in Biomedical Research?
Zifeng Wang, Benjamin Danek, Ziwei Yang +2
Data science plays a critical role in biomedical research, but it requires professionals with expertise in coding and medical data analysis. Large language models (LLMs) have shown…
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…
BernGraph: Probabilistic Graph Neural Networks for EHR-based Medication Recommendations
Xihao Piao, Pei Gao, Zheng Chen +4
The medical community believes binary medical event outcomes in EHR data contain sufficient information for making a sensible recommendation. However, there are two challenges to e…
MLOmics: Cancer Multi-Omics Database for Machine Learning
Ziwei Yang, Rikuto Kotoge, Xihao Piao +6
Framing the investigation of diverse cancers as a machine learning problem has recently shown significant potential in multi-omics analysis and cancer research. Empowering these su…