Artificial Intelligence in Disease Diagnosis, Treatment, Risk Forecast, and Health Informatics
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: closed (10 January 2022) | Viewed by 575
Special Issue Editors
Interests: bioinformatics; artificial intelligence; disease diagnosis; treatment; risk Forecast, and health informatics
Interests: nephrology; hemodialysis; peritoneal dialysis
Interests: algorithm design; machine learning; data mining
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue of the journal Applied Sciences, entitled “Artificial Intelligence in Diseases Diagnosis, Treatment, Risk Forecast, and Health Informatics”, aims to present recent advances in artificial intelligence techniques for disease diagnosis, treatment, risk forecast, and health informatics. The recent advances of artificial intelligence techniques, mostly based on machine learning, have significantly influenced the design and performance of computer-aided disease diagnosis, treatment, risk forecast, and health informatics. This Special Issue places particular attention on contributions dealing with practical applications, in which artificial intelligence techniques play a key role and achieve state-of-the-art performances. All interested authors are invited to submit their newest results on disease diagnosis, treatment, risk forecast, and health informatics for possible publication in this Special Issue. All papers need to present original, previously unpublished work and will be subject to the normal standards and peer-review processes of this journal. Potential topics include, but are not limited to: ·
- Disease diagnosis
- Treatment
- Risk forecast
- Health informatics
- Machine learning in disease diagnosis, treatment, risk forecast, and health informatics.
Prof. Dr. Cheng-Hong Yang
Dr. Jin-Bor Chen
Dr. Yu-Da Lin
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning
- deep learning
- statistical methods
- diseases diagnosis
- treatment and risk forecast
- health informatics
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