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    Research Interest​s

    • I was fortunate to have Prof. Mong-Na Lo Huang as my advisor during my graduate studies and to receive her guidance. Currently, I am a Ph.D. student at Stevens Institute of Technology, where I am advised by Prof. Feng Liu.
    • My research interests involve the application of machine learning to medical images and clinical data. Research areas include EHR data, Multimodal, and Graph Representation Learning.

    [Grant]

    I am currently leading an AI research team and project in collaboration with Taiwan's Far Eastern Memorial Hospital, Dr. Hung, Prof. Chen Ling from National Yang Ming Chiao Tung University, and Prof. Wen-Chih Peng from the Department of Computer Science. I am honored to have received funding and research support.

     

     

     

     

     

  • Publications

    • [12/2024]: One paper is accepted to AAAI'25 AISI [New!!]
    • [09/2024]: One paper is accepted to IEEE JBHI (IF:7.021) [New!!]
    • [08/2024]: One paper is accepted to Scientific Reports - Nature (IF:4.6) [New!!]
    • [07/2024]: One paper is accepted to CIKM'24 (Short paper, Acceptance Rate: 27%) [New!!]
    • [07/2024]: One paper is accepted to CIKM'24 (Demo paper) [New!!]
    • [04/2024]: One paper is accepted to CVPR'24 MMFM Workshop (Poster) [New!!]
    • [02/2024]: One paper is accepted to ISBI'24 (Oral presentation) [New!!]
    • [02/2023]: One paper is accepted to AAAI'23 (Student abstract)
    • [08/2022]: One paper is accepted to JFMA (Correspondence paper)
    • [05/2021]: One paper is accepted to MIUA 2021 (Oral paper)
    • [04/2021]: One paper is accepted to SIGIR 2021 (Short paper)

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    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, and Feng Liu

    Journal of Biomedical and Health Informatics (JBHI)

    https://ieeexplore.ieee.org/document/10694804

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

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

    33rd ACM International Conference on

    Information and Knowledge Management (CIKM 2024)

    https://arxiv.org/pdf/2407.12309

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    Large Language Multimodal Models for New-Onset Type 2 Diabetes Prediction using Five-Year Cohort Electronic Health Records

    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, and Fang-Ming Hung

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    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

    International Symposium on Biomedical Imaging (ISBI 2024)

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    Sequential graph attention learning for predicting dynamic stock trends

     

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

    Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023)

    https://ojs.aaai.org/index.php/AAAI/article/view/26982

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    Hospital transfer risk scoring system for a Taiwan COVID-19 medicalized hotel based on graph convolutional networks

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

    Journal of the Formosan Medical Association (JFMA 2021)

    https://www.sciencedirect.com/science/article/pii/S0929664622003230

     

    (Covid-19 AI scoring system : http://med-ai-demo.lab.nycu.edu.tw/)

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    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, and Chien-Ching Hsu

    The 25th UK Conference on Medical Image Understanding and Analysis (MIUA 2021)

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

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

    The 44th International ACM SIGIR Conference
    on Research and Development in Information Retrieval (SIGIR 2021)

    https://dl.acm.org/doi/10.1145/3404835.3463087

  • Conference/Journal Review

    • Reviewer: Machine Learning for Health Symposium (ML4H 2024)
    • Reviewer: Medical Image Computing and Computer Assisted Intervention (MICCAI 2024)
  • Education

    MS., Department of Applied Mathematics, National Sun Yat-sen University, Taiwan (2018 – 2020)

  • Research Descriptions

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    Far Eastern Memorial Hospital-Medical Research Department Clerk

    Development of a platform for predicting disease risk based on deep learning from electronic medical records.

    111/03-

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    E.SUN bank recommendation system

    110/01-110/12

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    Intern

    108/6-108/12

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    Asset Prices Effect of Monetary Policy and its Sectoral Difference

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    PM2.5 Data Analysis and Building IoT Projects

  • Work Experience

    Research Assistant

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    Institute of Hospital and Health Care Administration

    Our lab develops AI algorithms for CT scans and MRI images in collaboration with Far Eastern Hospital.

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    Research Assistant

    Work on Research Center for Information Technology Innovation

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    Intern

    Established in June 2016, Wellgen Medical Co., Ltd. has team members from academic, business, medical and technological fields. We have professional background, management expertise, and great execution. We focus on identification and analysis of medical microscopic images for disease detections. Using our revolutionary automated microscope, we are able to scan microscopic images at client side and analyze on the server by cloud computing using our artificial intelligence (AI) algorithm and big data analysis. Our automated microscope system and cloud computing service can improve diagnostic sensitivity and clinical outcome.

  • Ping me

  • Find me

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    Facebook

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    Twitter

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    LinkedIn