Yang Weiyi

Yang Weiyi

Yang Weiyi, Ph.D., is currently a lecturer at the School of Artificial Intelligence of Nanjing University of Information Science & Technology, a core member of the Jiangsu University Key Laboratory of Intelligent Medical Image Computing and the Smart Medical Research Institute, and a youth committee member of the Chinese Research Hospital Association. He graduated from the School of Communication Engineering of Jilin University with a bachelor’s degree and a doctoral degree, and received his doctorate in October 2022. He went to the Department of Biomedical Engineering at McGill University for joint training and studied under Robert E Kearney, an academician of the Canadian Academy of Engineering and an academician of the American Academy of Biomedical Sciences. Now he is mainly engaged in research in the fields of biomedical signal processing and the development of intelligent diagnostic systems. Currently, he is presiding over the Jiangsu Provincial Basic Research Program Natural Science Foundation (2024.09-2027.08). He has published more than 20 SCI academic papers in high-level international journals such as “Information Sciences”, “Knowledge-based systems”, and “Artificial intelligence in medicine”. Google Scholar shows that the paper has been cited more than 500 times, with the highest number of citations for a single article being 152 times. He has served as a reviewer for high-level SCI journals such as Information Fusion and Information Sciences. Has applied for multiple invention patents, 4 of which have been authorized.

For more information, please visit my personal homepage: https://faculty.nuist.edu.cn/yangweiyi/zh_CN/index.htm

Research direction:

Multi-mode electrophysiological signal processing: intelligent processing and classification of ECG, PCG, PPG and other electrophysiological signals;

Intelligent diagnosis of cardiovascular diseases: Intelligent diagnosis, classification and staging of arrhythmia, coronary heart disease, myocardial infarction, heart failure and other diseases;

Identification: ECG-based identification;

Diagnosis of other diseases.

Representative papers:

[1] Yang Weiyi , et al. “Automated atrial fibrillation and ventricular fibrillation recognition using a multi-angle dual-channel fusion network.” Artificial intelligence in medicine , 2023, 102680. [2] Yang Weiyi , et al. “A novel method for automated congestive heart failure and coronary artery disease recognition using THC-Net.” Information Sciences, 2021, 568, 427-447. [3] Yang Weiyi , et al. “Automated intra-patient and inter-patient coronary artery disease and congestive heart failure detection using EFAP-Net.” Knowledge-Based Systems, 2020, 201: 106083.

[4] Yang Weiyi , et al. “Automatic recognition of arrhythmia based on principal component analysis network and linear support vector machine” Computers in biology and medicine, 2018, 101: 22-32.

[5] Yang Weiyi , et al. “A novel method for identifying electrocardiograms using an independent component analysis and principal component analysis network.” Measurement, 2020, 152, 107363.

[6] Yang Weiyi , et al. “Automatic recognition of coronary artery disease and congestive heart failure using a multi-granularity cascaded hybrid network.” Biomedical signal processing and control , 2023, 105332.

[7] Yang Weiyi , et al. “Detection of differences of cardiorespiratory metrics between non-invasive respiratory support modes using machine learning methods.” Biomedical signal processing and control , 2023, 105028.

Translated from the original Chinese source.

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