Artificial Intelligence and Decision Support Systems
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 2276
Special Issue Editors
Interests: cloud computing; edge and fog computing; large-scale data processing; mobile device forensics; resource management systems; decision support systems; medical informatics
Special Issues, Collections and Topics in MDPI journals
Interests: business process management; knowledge abstraction and formalization through ontologies; decision support systems in healthcare; hematological clinical trials on multiple myeloma; deep/machine learning in healthcare; medical informatics and multicriteria data structures for compression and optimization algorithms
Interests: medical process management; deep/machine learning; case-based reasoning; decision support systems; medical informatics
Special Issue Information
Dear Colleagues,
Artificial Intelligence (AI) has quickly become an essential tool for decision making across various domains. In particular, Decision Support Systems (DSS) have enhanced decision making by leveraging AI techniques to analyze complex data, automate processes, and provide valuable recommendations, unlocking new capabilities for data analysis, pattern recognition, and prediction.
We invite researchers, practitioners, and academics from diverse disciplines to contribute original and innovative research papers to this Special Issue, presenting state-of-the-art technologies, methodologies, and case studies related to AI and its application in DSSs. We welcome papers covering any aspect of AI in DSS, including, but not limited to, the following topics:
- Machine learning and deep learning techniques for decision support;
- Knowledge-based DSSs;
- Explainable AI in decision support;
- Intelligent data analytics and visualization for decision making;
- Ethical considerations and social implications of AI in decision making;
- Intelligent DSSs in human-computer interaction;
- Intelligent DSSs in practical domains (e.g., healthcare, finance, and supply chain management).
The submitted papers should present original research contributions, describe innovative concepts, and demonstrate practical applications or theoretical advancements. Both theoretical and applied studies are welcome. The authors are encouraged to highlight the impact and relevance of their research in both academia and industry.
Dr. Marco Guazzone
Dr. Manuel Striani
Prof. Dr. Stefania Montani
Guest Editors
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. Information is an international peer-reviewed open access monthly 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 1600 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.
Keywords
- decision support systems
- artificial intelligence
- data-driven AI
- knowledge representation
- explainable AI DSS
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