Titlebook: Signal Processing Techniques for Computational Health Informatics; Md Atiqur Rahman Ahad,Mosabber Uddin Ahmed Book 2021 Springer Nature Sw

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,Artificial Intelligence, Machine Learning and Reasoning in Health Informatics—Case Studies,ith multivariate information coming from heterogeneous sources e.g. sensor signals, text, etc. This book chapter presents the research development of AI, ML and MR as applications in health informatics. Five case studies on health informatics have been discussed and presented as (1) advanced Parkins

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Risk Prediction with Machine Learning in Cesarean Section: Optimizing Healthcare Operational Decisining (ML) algorithms, it is being used for the complex, multidimensional and large data in healthcare systems. Cesarean section or C-section is the widely used method when any abnormality affects the normal birth of a child. The aim of this research is to identify the cesarean section of child birth

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,Artificial Intelligence, Machine Learning and Reasoning in Health Informatics—An Overview,or the ability to apply prior knowledge to new situations with adaptation and changes. This book chapter presents some AI, ML and MR techniques and approached those are widely used in health informatics domains. Here, the overview of each technique is discussed to show how they can be applied in the development of a decision support system.

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Mental Health and Sensing, toward these detection methods. We also see available methods of therapeutic treatment available through digital means. We highlight a few key intervention technologies that are being developed by researchers to fight against mental illness issues.

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1868-4394 rmatics in the big data age.Discusses the incorporation of r.This book focuses on signal processing techniques used in computational health informatics. As computational health informatics is the interdisciplinary study of the design, development, adoption and application of information and technolo

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Book 2021ary study of the design, development, adoption and application of information and technology-based innovations, specifically, computational techniques that are relevant in health care, the book covers a comprehensive and representative range of signal processing techniques used in biomedical applica

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Time-Frequency Analysis in Health Informatics,especially useful for health informatics. The last part of the chapter also addresses more advanced techniques and few examples. The chapter should come to be useful for those who consider these techniques for their applications.

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Entropy Analysis in Health Informatics,presented. Then, more and very recent entropy measures are exposed and some of their used in health informatics are listed. This is performed from two points of view: for time series (uni-dimensional data) and for images (bi-dimensional data).