
Medical Data Analysis and Processing using Explainable Artificial Intelligence
- 252 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Medical Data Analysis and Processing using Explainable Artificial Intelligence
About this book
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.
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Information
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Table of Contents
- Preface
- About the Editors
- List of Contributors
- Chapter 1 Explainable AI (XAI) Concepts and Theory
- Chapter 2 Utilizing Explainable Artificial Intelligence to Address Deep Learning in Biomedical Domain
- Chapter 3 Explainable Fuzzy Decision Tree for Medical Data Classification
- Chapter 4 Statistical Algorithm for Change Point Detection in Multivariate Time Series of Medicine Data Based on Principles of Explainable Artificial Intelligence
- Chapter 5 XAI and Machine Learning for Cyber Security: A Systematic Review
- Chapter 6 Classification and Regression Tree Modelling Approach to Predict the Number of Lymph Node Dissection among Endometrial Cancer Patients
- Chapter 7 Automated Brain Tumor Analysis Using Deep Learning-Based Framework
- Chapter 8 A Robust Framework for Prediction of Diabetes Mellitus Using Machine Learning
- Chapter 9 Effective Feature Extraction for Early Recognition and Classification of Triple Modality Breast Cancer Images Using Logistic Regression Algorithm
- Chapter 10 Machine Learning and Deep Learning Models Used to Detect Diabetic Retinopathy and Its Stages
- Chapter 11 Clinical Natural Language Processing Systems for Information Retrieval from Unstructured Medical Narratives
- Index