Special Issue on Data Science for Smart Healthcare: Methodologies and Applications
• 大类 : 工程技术 - 2区
• 小类 : 计算机：理论方法 - 2区
Healthcare applications around the world are facing new challenges in responding to trends of aging population, the rise of chronic diseases, resources constraints, and the growing focus of citizens on healthy living and prevention.
Therefore, there is an increasing focus on how to improve the rate of fast and accurate diagnoses, how to reduce costs and outcomes in health systems and how to get people to take more accountability for their own health.
Novel ICT technology are enabling the collection of more data than ever before, including medical health records, people’s vital signs and their lifestyle and data about health systems.
This great amount of data does not immediately result in better healthcare insights, but, on the contrary, if not used properly, it can be a burden to people and result in clinicians spending more time with computers than face to face with patients, or citizens being lost in data they are getting from health trackers and many different sensors, or, again, patients reluctant to accept assistive technologies.
In this perspective Data Science and Machine Learning can provide benefits to both patient and medical professionals, also helping in answering the abovementioned questions related to the large amount of available data.
The objective of this special issue is to attract high-quality research and survey articles that promote research and reflect the most recent advances in addressing Data Science methodologies and applications for Healthcare.
We welcome researchers from both academia and industry to provide their state-of-the-art technologies and ideas covering all aspects of Data Science methodologies and applications for Healthcare.
Potential topics include but are not limited to following:
• Artificial Intelligence models for Healthcare.
• Machine Learning models for Healthcare.
• Clustering and classification algorithms for Healthcare.
• Deep and reinforcement learning for Healthcare.
• Big Data analytics for data processing from Healthcare.
• Fuzzy Systems proposals for Healthcare.
• Expert/hybrid Systems for Healthcare
• AI/ML for IoT, Industry 4.0 for Healthcare
• Intelligent security proposals for Healthcare.
• Control systems developments for Healthcare
• Organization Based Multiagent Systems for Healthcare