Artificial Intelligence in Healthcare and Medicine

by Kayvan Najarian (Editor), Delaram Kahrobaei (Editor), Enrique Dominguez (Editor), Reza Soroushmehr (Editor)

Overview

This book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also:

• Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine
• Examines the advancements, challenges, and opportunities of using AI in medical and health applications
• Includes 10 cases for practical application and reference

Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor.

Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York.

Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga.

Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.

Product Details

ISBN-13:	9780367619176
Publisher:	CRC Press
Publication date:	04/15/2022
Pages:	300
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor.

Professor Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY and the former Chair of Cyber Security, University of York.

Enrique Domínguez is an associate professor at the department of Computer Science at the University of Malaga and a member of Biomedic Research Institute of Malaga.

Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.

Table of Contents

1. Machine learning for disease classification: A perspective. 2. A review of automatic cardiac segmentation using deep learning and deformable models. 3. Advances in artificial intelligence applied to heart failure. 4. A Combination of Dilated Adversarial Convolutional Neural Network and Guided Active Contour Model for Left Ventricle Segmentation. 5. Automated methods for vessel segmentation in X-ray coronary angiography and geometric modeling of coronary angiographic image sequences: a survey. 6. Super-Resolution of 3D Magnetic Resonance Images of the Brain. 7. Head CT analysis for intracranial hemorrhage segmentation. 8. Wound Tissue Classification with Convolutional Neural Networks. 9. Artificial Intelligence Methodologies in Dentistry. 10. Literature Review of Computer Tools for the Visually Impaired: A Focus on Search Engines. 11. Tensor methods for clinical informatics.