Jun-En Ding

According to our database, Jun-En Ding authored at least 29 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

CURENet: combining unified representations for efficient chronic disease prediction.

Cong-Tinh Dao, Nguyen-Minh-Thao Phan, Jun-En Ding, Chenwei Wu, David S. Restrepo, Dongsheng Luo, Fanyi Zhao, Chun-Chieh Liao, Wen-Chih Peng, Chi-Te Wang, Pei-Fu Chen, Ling Chen, Xinglong Ju, Feng Liu, Fang-Ming Hung

Health Inf. Sci. Syst., December, 2026

NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectro-Spatial Grounding and Temporal State-Space Reasoning.

Guoan Wang, Shihao Yang, Jun-En Ding, Hao Zhu, Feng Liu

CoRR, March, 2026

Chain-of-Thought Reasoning with Large Language Models for Clinical Alzheimer's Disease Assessment and Diagnosis.

Tongze Zhang, Jun-En Ding, Melik Ozolcer, Fang-Ming Hung, Albert Chih-Chieh Yang, Feng Liu, Yi-Rou Ji, Sang Won Bae

CoRR, February, 2026

NeuroWeaver: An Autonomous Evolutionary Agent for Exploring the Programmatic Space of EEG Analysis Pipelines.

Guoan Wang, Shihao Yang, Jun-En Ding, Hao Zhu, Feng Liu

CoRR, February, 2026

Enhancing multimodal medical image classification through cross-graph modal contrastive learning.

Jun-En Ding, Chien-Chin Hsu, Chi-Hsiang Chu, Shuqiang Wang, Feng Liu

Expert Syst. Appl., 2026

2025

CURENet: Combining Unified Representations for Efficient Chronic Disease Prediction.

Cong-Tinh Dao, Nguyen Minh Thao Phan, Jun-En Ding, Chenwei Wu, David S. Restrepo, Dongsheng Luo, Fanyi Zhao, Chun-Chieh Liao, Wen-Chih Peng, Chi-Te Wang, Pei-Fu Chen, Ling Chen, Xinglong Ju, Feng Liu, Fang-Ming Hung

CoRR, November, 2025

Foundation and Large-Scale AI Models in Neuroscience: A Comprehensive Review.

Shihao Yang, Xiying Huang, Danilo Bernardo, Jun-En Ding, Andrew Michael, Jingmei Yang, Patrick Kwan, Ashish Raj, Feng Liu

CoRR, October, 2025

Variational Mixture of Graph Neural Experts for Alzheimer's Disease Biomarker Recognition in EEG Brain Networks.

Jun-En Ding, Anna Zilverstand, Shihao Yang, Albert Chih-Chieh Yang, Feng Liu

CoRR, October, 2025

RPRO:Ranked Preference Reinforcement Optimization for Enhancing Medical QA and Diagnostic Reasoning.

Chia-Hsuan Hsu, Jun-En Ding, Hsin-Ling Hsu, Feng Liu, Fang-Ming Hung

CoRR, September, 2025

Flexible and Explainable Graph Analysis for EEG-based Alzheimer's Disease Classification.

Jing Wang, Jun-En Ding, Feng Liu, Elisa Kallioniemi, Shuqiang Wang, Wen-Xiang Tsai, Albert C. Yang

CoRR, April, 2025

MedPlan:A Two-Stage RAG-Based System for Personalized Medical Plan Generation.

Hsin-Ling Hsu, Cong-Tinh Dao, Luning Wang, Zitao Shuai, Thao Nguyen Minh Phan, Jun-En Ding, Chun-Chieh Liao, Pengfei Hu, Xiaoxue Han, Chih-Ho Hsu, Dongsheng Luo, Wen-Chih Peng, Feng Liu, Fang-Ming Hung, Chenwei Wu

CoRR, March, 2025

NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders.

Jun-En Ding, Dongsheng Luo, Anna Zilverstand, Feng Liu

CoRR, February, 2025

Spatial Craving Patterns in Marijuana Users: Insights From fMRI Brain Connectivity Analysis With High-Order Graph Attention Neural Networks.

Jun-En Ding, Shihao Yang, Anna Zilverstand, Kaustubh R. Kulkarni, Xiaosi Gu, Feng Liu

IEEE J. Biomed. Health Informatics, January, 2025

NeuroTree: Hierarchical Functional Brain Pathway Decoding for Mental Health Disorders.

Jun-En Ding, Dongsheng Luo, Chenwei Wu, Feng Liu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

No Black Boxes: Interpretable and Interactable Predictive Healthcare with Knowledge-Enhanced Agentic Causal Discovery.

Xiaoxue Han, Pengfei Hu, Chang Lu, Jun-En Ding, Feng Liu, Yue Ning

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

MedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation.

Hsin-Ling Hsu, Cong-Tinh Dao, Luning Wang, Zitao Shuai, Thao Nguyen Minh Phan, Jun-En Ding, Chun-Chieh Liao, Pengfei Hu, Xiaoxue Han, Chih-Ho Hsu, Dongsheng Luo, Wen-Chih Peng, Feng Liu, Fang-Ming Hung, Chenwei Wu

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track), 2025

Multi-OphthaLingua: A Multilingual Benchmark for Assessing and Debiasing LLM Ophthalmological QA in LMICs.

David S. Restrepo, Chenwei Wu, Zhengxu Tang, Zitao Shuai, Thao Nguyen Minh Phan, Jun-En Ding, Cong-Tinh Dao, Jack Gallifant, Robyn Gayle Dychiao, Jose Carlo Artiaga, André Hiroshi Bando, Carolina Pelegrini Barbosa Gracitelli, Vincenz Ferrer, Leo Anthony Celi, Danielle S. Bitterman, Michael G. Morley, Luis Filipe Nakayama

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive Learning.

Jun-En Ding, Chien-Chin Hsu, Feng Liu

CoRR, 2024

Large Language Multimodal Models for 5-Year Chronic Disease Cohort Prediction Using EHR Data.

Jun-En Ding, Phan Nguyen Minh Thao, Wen-Chih Peng, Jian-Zhe Wang, Chun-Cheng Chug, Min-Chen Hsieh, Yun-Chien Tseng, Ling Chen, Dongsheng Luo, Chi-Te Wang, Pei-Fu Chen, Feng Liu, Fang-Ming Hung

CoRR, 2024

Identification of Craving Maps among Marijuana Users via the Analysis of Functional Brain Networks with High-Order Attention Graph Neural Networks.

Jun-En Ding, Shihao Yang, Anna Zilverstand, Feng Liu

CoRR, 2024

Parkinson's Disease Classification Using Contrastive Graph Cross-View Learning with Multimodal Fusion of Spect Images and Clinical Features.

Jun-En Ding, Chien-Chin Hsu, Feng Liu

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

MEDFuse: Multimodal EHR Data Fusion with Masked Lab-Test Modeling and Large Language Models.

Phan Nguyen Minh Thao, Cong-Tinh Dao, Chenwei Wu, Jian-Zhe Wang, Shun Liu, Jun-En Ding, David S. Restrepo, Feng Liu, Fang-Ming Hung, Wen-Chih Peng

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

EHR-Based Mobile and Web Platform for Chronic Disease Risk Prediction Using Large Language Multimodal Models.

Chun-Chieh Liao, Wei-Ting Kuo, I-Hsuan Hu, Yen-Chen Shih, Jun-En Ding, Feng Liu, Fang-Ming Hung

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Parkinson Disease classification Using Contrastive Graph Cross-View Learning with Multimodal Fusion of SPECT Images and Clinical Features.

Jun-En Ding, Chien-Chin Hsu, Feng Liu

CoRR, 2023

Hospital transfer risk prediction for COVID-19 patients from a medicalized hotel based on Diffusion GraphSAGE.

Jun-En Ding, Chih-Ho Hsu, Kuan-Chia Ling, Ling Chen, Fang-Ming Hung

CoRR, 2023

Sequential Graph Attention Learning for Predicting Dynamic Stock Trends (Student Abstract).

Tzu-Ya Lai, Wen Jung Cheng, Jun-En Ding

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

An Exploration Study of Multi-stage Conversational Passage Retrieval: Paraphrase Query Expansion and Multi-view Point-wise Ranking.

Jia-Huei Ju, Chih-Ting Yeh, Cheng-Wei Lin, Chia-Ying Tsao, Jun-En Ding, Chuan-Ju Wang, Ming-Feng Tsai

Proceedings of the Thirtieth Text REtrieval Conference, 2021

LSTPR: Graph-based Matrix Factorization with Long Short-term Preference Ranking.

Chih-Hen Lee, Jun-En Ding, Chih-Ming Chen, Jing-Kai Lou, Ming-Feng Tsai, Chuan-Ju Wang

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Dopamine Transporter SPECT Image Classification for Neurodegenerative Parkinsonism via Diffusion Maps and Machine Learning Classifiers.

Jun-En Ding, Chi-Hsiang Chu, Mong-Na Lo Huang, Chien-Ching Hsu

Proceedings of the Medical Image Understanding and Analysis - 25th Annual Conference, 2021