Special Issue "Artificial Intelligence for Sustainable Services and Applications"
Deadline for manuscript submissions: 30 September 2021.
Interests: health informatics; artificial intelligence in medicine; Internet of Things; big data
Interests: machine learning; RFID; Internet of Things; health informatics; carsharing service
Interests: E-health; mobile health
We have recently seen rapid development of healthcare technologies, along with the extensive adoption of the Internet, mobile technologies, data analytics, and artificial intelligence (AI) in healthcare. These advancements have resulted in highly multi-disciplinary research in digital, mobile, and smart health, and have also led the move in the direction of more personalized care. Sustainability simultaneously has the ability to meet our present needs without compromising future generations meeting their own needs (Brundtland Commission 1987), and it covers the following three aspects: environmental, social, and economic. Furthermore, the healthcare industry has consumed a tremendous amount of energy and water, and has produced a considerable amount of waste. Thus, it is necessary for the healthcare industry to be more responsible by adopting sustainable practices in order to efficiently utilize its resources and minimize environmental impacts.
This Special Issue aims to cover recent advances in artificial intelligence (AI) for healthcare with a sustainability perspective in mind, from both academic researchers and industry developers. Any type of article aligned with the journal (original research, case study, technical report, short communication, and reviews) is welcome for this Special Issue. Topics of interests include, but are not limited to, the following:
- Health informatics
- Artificial intelligence in healthcare
- Personalized healthcare
- Incorporating sustainable practices in healthcare
- Sustainable healthcare services and applications
- Electronic and mobile health
- Clinical decision support systems
- IoT and big data in healthcare
- Machine learning and deep learning in healthcare
- Descriptive, diagnostic, predictive analytics in healthcare
- Data security and privacy in healthcare
- Machine learning to understand human behavior and well-being
- New algorithms for medical and healthcare data analytics
- Predictive analysis in personalized healthcare
Dr. Muhammad Syafrudin
Dr. Ganjar Alfian
Prof. Dr. Muhammad Anshari
Assoc. Prof. Dr. Tony Hadibarata
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 papers will be 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. Sustainability 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 1900 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.
- health informatics
- artificial intelligence in medicine
- sustainable healthcare
- mobile health
- clinical decision support systems
- healthcare applications and services
- IoT and big data in healthcare