Intelligent Learning and Health Diagnosis Technologies

Dear Colleagues,

With the growth of the world’s population and the increasing demand for human health, the diagnosis of a large number of patients has placed great pressure on public health institutions. For some diseases, it is difficult to diagnose them quickly and accurately. In recent years, artificial intelligence technologies have been developing quickly and have seen successful applications in many areas. Inspired by artificial intelligence technologies, intelligent diagnosis technologies (e.g., medical image recognition, brain–computer interface, neuro-feedback) could help to diagnose some diseases quickly and accurately. To promote the development of intelligent diagnosis technologies, this Special Issue will focus on various new technologies and methods that could help to improve the performance of intelligent diagnosis. In particular, this Special Issue welcomes contributions on topics including but not limited to:

• Medical imaging analysis and diagnosis methods;
• Machine learning algorithms for medical diagnosis;
• Deep learning methods for medical diagnosis;
• Brain–computer interface technologies for medical applications;
• Neuro-feedback technologies for medical diagnosis;
• Applications of various intelligent technologies in medical diagnosis;
• Review/survey articles.

Prof. Dr. Jing Jin
Prof. Dr. Ali Zemouche
Dr. Ian Daly
Prof. Dr. Peng Xu
Dr. Ren Xu
Prof. Dr. Feng Duan
Prof. Dr. Junfeng Sun
Guest Editors

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