Special Issue "Computing and Artificial Intelligence Techniques for Healthcare Applications: Second Edition"
Deadline for manuscript submissions: 31 December 2023 | Viewed by 22119
Interests: quantum information and computation; information security and privacy
Special Issues, Collections and Topics in MDPI journals
Special Issue in Healthcare: Computing and Artificial Intelligence Techniques for Healthcare Applications
Special Issue in Electronics: AI-Driven Cybersecurity Solutions for Next Generation-5G/6G Enabled Cyber Physical Systems
With the rapid growth of biological data in recent years, data-driven computational methods are increasingly needed to analyze large-scale biological data quickly and accurately. Biological and medical technologies in particular have been providing us with explosive volumes of biological and physiological data, such as medical images, electroencephalography signals, and genomic and protein sequences. Learning from these data will facilitate our understanding of human health and disease. Accordingly, computation and machine learning techniques have recently emerged in both academia and industry as “intelligent” methods in many specific healthcare areas to gain insight from medical and biological data. To expand the scope and ease of the applicability of machine learning, it is highly desirable to make learning algorithms less dependent on handcrafted feature engineering, so that novel applications can be constructed faster and, more importantly, progress toward artificial intelligence (AI) can be made.
This Special Issue aims to target recent computation and machine learning techniques as well as state-of-the-art applications in healthcare areas such as bioinformatics, bioprocess systems, biomedical systems, biomedical physics, and bioecological systems. This Special Issue will consider original research articles and review articles on computational and intelligent methods in healthcare and their applications. We wish to gather relevant contributions introducing new techniques for the study of complex healthcare systems driven by computational methods. Papers on interdisciplinary applications are particularly welcome. We also encourage authors to make their codes and experimental data available to the public, so that our Special Issue can be more infusive and attractive.
Dr. Ahmed Farouk
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Healthcare is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- quantum machine learning
- supervised learning algorithms
- unsupervised learning algorithms
- imbalanced learning algorithms
- multiview feature learning
- deep-learning-based feature learning strategies
- feature representation optimization algorithms
- handcrafted feature representation algorithms
- computational and mathematical techniques
- image and signal processing
- mental health
- bioprocess systems
- biomedical systems
- biomedical physics
- bioecological systems