Medical Data Analysis and Processing Using Explainable Artificial Intelligence
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The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical.
- Present explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science.
- Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications.
- Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data.
- Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing.
- Discusses machine learning and deep learning scalability models in healthcare systems.
This text focusses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.
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