Jena O.P., Panda M., Kose U. (eds.) Medical Data Analysis and Processing using Explainable Artificial Intelligence

Boca Raton: CRC Press, 2023. — 269 p.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.
Presents 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 focuses 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.Preface
About the Editors
List of Contributors
Explainable AI (XAI) Concepts and Theory
Utilizing Explainable Artificial Intelligence to Address Deep Learning in Biomedical Domain
Explainable Fuzzy Decision Tree for Medical Data Classification
Statistical Algorithm for Change Point Detection in Multivariate Time Series of Medicine Data Based on Principles of Explainable Artificial Intelligence
XAI and Machine Learning for Cyber Security: A Systematic Review
Classification and Regression Tree Modelling Approach to Predict the Number of Lymph Node Dissection among Endometrial Cancer Patients
Automated Brain Tumor Analysis Using Deep Learning-Based Framework
A Robust Framework for Prediction of Diabetes Mellitus Using Machine Learning
Effective Feature Extraction for Early Recognition and Classification of Triple Modality Breast Cancer Images Using Logistic Regression Algorithm
Machine Learning and Deep Learning Models Used to Detect Diabetic Retinopathy and Its Stages
Clinical Natural Language Processing Systems for Information Retrieval from Unstructured Medical Narratives
Index