Assist. Prof. Dr. Yen-Chein Lai | Developmental Neuroscience | Research Excellence Award
Assist. Prof. Dr. Yen-Chein Lai | Chung Shan Medical University | Taiwan
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Dr. Hendry Ramly is a clinician–researcher with advanced training in general medicine, cardiology, and intensive care medicine, and a focused academic interest in non-traumatic out-of-hospital cardiac arrest and post-resuscitation care. His research is directly informed by frontline clinical practice across acute medicine, ICU, and cardiology, where he manages critically ill patients following cardiac arrest. Dr. Ramly’s primary research examines cardiovascular management strategies after return of spontaneous circulation, with particular emphasis on haemodynamic stabilisation, coronary pathology, and the timing and utility of urgent coronary angiography. Neurological outcomes are included as standard clinical endpoints, while the central focus remains on cardiovascular determinants of survival and in-hospital mortality. He is lead author of a retrospective observational cohort study published in Heart, Lung and Circulation (2025), evaluating outcomes of non-traumatic out-of-hospital cardiac arrest at a tertiary centre. His additional audit work includes thoracic surgical outcomes, geriatric referral pathways, and procedural adequacy in respiratory medicine. Through clinically driven research and multidisciplinary collaboration, Dr. Ramly aims to refine evidence-based pathways that improve survival, decision-making, and quality of care for patients following cardiac arrest.
Multiple sclerosis and the association with inflammatory bowel disease: Results from a retrospective cohort study. (2025). Multiple Sclerosis and Related Disorders.
Cytokine release syndrome risk model with T-cell engaging therapies. (2025). Cytotherapy.
Evaluating the accuracy of responses by large language models for information on disease epidemiology. (2025). Pharmacoepidemiology and Drug Safety.
1. Mazrooei Rad, E., Mazinani, S. M., & Zendehbad, S. A. (2025). Diagnosis of Alzheimer’s disease using non-linear features of ERP signals through a hybrid attention-based CNN-LSTM model. Computer Methods and Programs in Biomedicine Update, 5, 100192.
2. Zendehbad, S. A., Sharifi Razavi, A., Tabrizi, N., & Sedaghat, Z. (2025). A systematic review of artificial intelligence techniques based on electroencephalography analysis in the diagnosis of epilepsy disorders: A clinical perspective. Epilepsy Research, 207, 107582.
3. Mazrooei Rad, E., Zendehbad, S. A., & Hosseinzadeh, V. (2025). Fetal QRS complex detection based on adaptive filters and peak detection. Research on Biomedical Engineering, 41(3), 424–438.
4. Zendehbad, S. A., Ghasemi, J., & Samsami Khodadad, F. (2025). FatigueNet: A hybrid graph neural network and transformer framework for real-time multimodal fatigue detection. Scientific Reports, 15(1), 640.
5. Safdel, A., Zendehbad, S. A., & Ghasemi, J. (2025). Advanced deep learning approaches for accurate and efficient suspicious behavior detection in surveillance videos. Computational Sciences and Engineering, 21(2), 1099.
(2025). Effects of exposure to air pollution and cold weather on acute myocardial infarction mortality. Atmosphere.
(2025). The risk of ischemic stroke in patients with chronic obstructive pulmonary disease and atrial fibrillation. Life.
(2024). Increased risk of psychiatric disorder in patients with hearing loss: A nationwide population-based cohort study. Journal of Translational Medicine.
(2024). Diabetes mellitus and gynecological and inflammation disorders increased the risk of pregnancy loss in a population study. Life.
(2024). The influence of fine particulate matter and cold weather on emergency room interventions for childhood asthma. Life.
(2024). Impact of foodborne disease in Taiwan during the COVID-19 pandemic. Medicina (Lithuania).
(2024). Analyzing COVID-19 and air pollution effects on pediatric asthma emergency room visits in Taiwan. Toxics.
Deng, W. (2025). AI and knowledge sharing in team performance: Emotional intelligence as the mediator between coordination and performance. Sustainable Futures.
Deng, W., & Jiang, M. (2025). A multilevel fuzzy AHP model for green furniture evaluation: Enhancing resource efficiency and circular design through lifecycle integration. Systems.
Jiang, M., Deng, W., & Lin, H. (2024). Sustainability through biomimicry: A comprehensive review of bionic design applications. Biomimetics.
Dr. Yue Ding is a distinguished neuroscientist and biomedical engineer whose research focuses on the neural mechanisms of music and rhythm-based interventions for affective and anxiety disorders, particularly in children and adolescents. With a Ph.D. in Neuroscience from Tsinghua University and a B.S. in Biomedical Engineering from Dalian University of Technology, Dr. Ding has extensive experience in both academic and industry settings, including leadership roles at Shanghai Mental Health Center, AI Institute at iFlytek, and Nielsen Consumer LLC, as well as a visiting scholar position at Johns Hopkins University. Dr. Ding’s research integrates neuroscience, artificial intelligence, and virtual reality to develop personalized interventions, including closed-loop music therapies, rhythm interactive training, and controllable music generation models, supported by numerous national and municipal grants. His work also explores neural oscillations in depression and anxiety, taste perception, and language impairments in Alzheimer’s patients. He is actively involved in professional organizations, including the Art Psychotherapy Committee, Music Psychology Committee, and editorial boards of prominent journals such as Scientific Reports and Frontiers in Psychiatry. With 17 published documents, Dr. Ding has garnered 228 citations and holds an h-index of 8, reflecting his influential contributions to the fields of neuroscience, neuroengineering, and mental health research.
Ding, Y., Hu, X., Li, J., Ye, J., Wang, F., & Zhang, D. (2018). What makes a champion: The behavioral and neural correlates of expertise in multiplayer online battle arena games. International Journal of Human–Computer Interaction, 34(8), 682–694.
Ding, Y., Hu, X., Xia, Z., Liu, Y. J., & Zhang, D. (2021). Inter-brain EEG feature extraction and analysis for continuous implicit emotion tagging during video watching. IEEE Transactions on Affective Computing, 12(1), 92–102.
Ding, Y., Zhang, Y., Zhou, W., Ling, Z., Huang, J., Hong, B., & Wang, X. (2019). Neural correlates of music listening and recall in the human brain. Journal of Neuroscience, 39(41), 8112–8123.
Ding, Y., Chu, Y., Liu, M., Ling, Z., Wang, S., Li, X., & Li, Y. (2022). Fully automated discrimination of Alzheimer’s disease using resting-state electroencephalography signals. Quantitative Imaging in Medicine and Surgery, 12(2), 1063–1077.
Ding, Y., Gray, K., Forrence, A., Wang, X., & Huang, J. (2018). A behavioral study on tonal working memory in musicians and non-musicians. PLOS ONE, 13(8), e0201765.
Zhang, Y., Ding, Y., Huang, J., Zhou, W., Ling, Z., Hong, B., & Wang, X. (2021). Hierarchical cortical networks of “voice patches” for processing voices in human brain. Proceedings of the National Academy of Sciences of the United States of America, 118(44), e2103518118.