Application of Decision Support Systems in Biomedical Engineering
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: 20 December 2024 | Viewed by 1468
Special Issue Editor
Interests: computer aided detection and diagnosis systems for biomedical signals; monitoring systems for health-care; analysis and synthesis of digital electronic systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the framework of healthcare facilities, the decision-making phase is frequent and of particular relevance to achieve results responding to expectations. The fusion of technology and medical science allowed for the development of decision support systems (DSSs) that are able to make good decisions in extremely complex and difficult medical diagnosis cases. Two different application contexts of DSSs can be configured, including the expert knowledge-provider context and the end user context. For example, a DSS could assist clinicians in solving diagnostic and therapeutic problems by making use of patient-related parameters as inputs which have to be combined with models and algorithms. The choice/adoption of a particular DSS depends on several criteria such as the complexity of the problem, the simplicity of the approach, the typology of data available, the expertise of the decision makers, and so on. A suitable and appropriate DSS has to be user-friendly and accurate.
This Special Issue addresses the most recent applications of decision support systems in biomedical engineering in the expert knowledge provider context and the end user context. Original high-quality papers and review articles are welcome and incentivized. In particular, topics of interest for this Special Issue include, but are not limited to, the following:
- Decision support systems for biomedical systems;
- Methods for the classification of biosignals;
- Biosignal/bioimage feature extraction;
- Algorithms to improve the quality of biosignals;
- Artificial Intelligence tools for biosignal/bioimage analysis
- Clinical decision support system;
- Medical healthcare systems.
Dr. Maria Rizzi
Guest Editor
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Keywords
- advanced healthcare methods
- biomedical image analysis
- computer-aided detection systems
- computer-aided diagnosis systems
- monitoring systems
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