Submission Deadline: 30 June 2023 (closed)
Today the human lives in the age of Information and technology. Information is the key, the power, and the engine that moves the world’s economy. The world is moving with markets data, medical epidemiologic sets, Internet browsing records, geological surveys data, complex engineering models, and so on. Health Sciences are fully embedded in information technology. Health science and Biology are very complex fields and have made a long walk from the ancient times, but processes involved in biology, medicine and physiology are much too intricate to be faithfully modeled. In the early eighties, AI in medicine was the main concern while developing medical expert systems in specialized medical domains aimed at supporting diagnostic decision-making. The main problems addressed at this early stage of expert system research concerned knowledge acquisition, knowledge representation, reasoning and explanation. Now there are many modern hospitals and health care institutions, which are well equipped with monitoring and other advanced data collection devices. The need of knowledge on the domain or on the data analysis process becomes essential in biomedical applications, as medical decision making needs to be supported by arguments based on basic medical and pharmacological knowledge.
The overall aim of this special issue is to collect state-of-the-art contributions on the latest research and development, up-to-date issues, and challenges in the field of Intelligent Biomedical Image Processing and Computer Vision and related applications. Proposed submissions should be original, unpublished, and present novel in-depth fundamental research contributions either from a methodological perspective or from an application point of view.
The topics of interest are strictly limited to:
• Computational intelligence in biological and clinical medicine
• Behavioral, Environmental, and Public health informatics
• Biological network modeling and analysis
• Biomedical imaging and data visualization
• Evolutionary algorithms for optimization methodologies for biomedical applications
• Data mining for health data processing and analysis on mobile devices
• Machine learning and deep learning for health-related mobile applications
• Intelligent medical information systems
• Predictive modeling and analytics in healthcare
• Virtual and augmented reality
• Medical image/signal analysis and processing
• Internet of health things
• Biomedical data pattern recognition
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