Manuscript Topics

Computer-Aided Detection (CADe) refers to a system that helps physicians to detect or discover medical abnormalities. Besides, Computer-Aided Diagnosis (CADx) refers to a system that helps physicians to identify the nature and cause of an illness. Both types of systems help doctors to make decisions quickly, through a second opinion that can improve the accuracy of decisions effectively and reduce the rate of misdiagnosis. They can be applied with any information obtained from patients such as images or ultrasound. In addition, both can be seen as Decision Support Systems (DSSs), that are increasingly important information systems that help to make decisions related to unstructured and semi-unstructured decision problems that do not have a simple solution from a human point of view. The architecture of a common DSS is basically composed of three main components which are very important research fields nowadays: (1) knowledge base; (2) user interface; and (3) model to infer the decisions. Such models may be based on multiple types of artificial intelligence-based algorithms, such as neural networks, logistic regression, classification trees, fuzzy logic, etc. Although there are multiple works that try to optimize the operation of decision support systems, researchers are still trying to optimize their performance by refining and proposing new algorithms that normally are adapted to the set of data available for a particular domain of knowledge. Thus, the aim of this Special Issue is to enhance the state-of-the-art in this area significantly, improving the performance of Computer-Aided Detection and Diagnosis systems. We encourage authors across the world to submit their original and unpublished works. We have a special interest in works focusing on the topics listed below, but we are open to other works that fit the theme of the Special Issue.

The topics of the Special Issue include, but are not limited to:  
• Computer-Aided Detection  
• Computer-Aided Diagnosis  
• Artificial Intelligence  
• Machine Learning  
• Health Informatics  
• Decision Support System

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