Machine learning in medicine. (2021)

• Record Type: Book
• Further Information: Note: Edited by Ayman El-Baz, Jasjit S. Suri.
• Editors: El-Baz, Ayman S; Suri, Jasjit S
• Contents: Preface Acknowledgements Editors Contributors Chapter 1 Another Set of Eyes in Anesthesiology Pushkar Aggarwal Chapter 2 Dermatological Machine Learning Clinical Decision Support System Pushkar Aggarwal Chapter 3 Vision and AI Mohini Bindal and Pushkar Aggarwal Chapter 4 Thermal Dose Modeling for Thermal Ablative Cancer Treatments by Cellular Neural Networks Jinao Zhang, Sunita Chauhan, Wa Cheung, and Stuart K. Roberts Chapter 5 Ensembles of Convolutional Neural Networks with Different Activation Functions for Small to Medium-Sized Biomedical Datasets Filippo Berno, Loris Nanni, Gianluca Maguolo, and Sheryl Brahnam Chapter 6 Analysis of Structural MRI Data for Epilepsy Diagnosis Using Machine Learning Techniques Seyedmohamm ad Shams, Esmaeil Davoodi-Bojd, and Hamid Soltanian-Zadeh Chapter 7 Artificial Intelligence-Powered Ultrasound for Diagnosis and Improving Clinical Workflow Zeynettin Akkus Chapter 8 Machine Learning for E/MEG-Based Identification of Alzheimer’s Disease Su Yang, Girijesh Prasad, KongFatt Wong-Lin, and Jose Sanchez-Bornot Chapter 9 Some Practical Challenges with Possible Solutions for Machine Learning in Medical Imaging Naimul Khan, Nabila Abraham, Anika Tabassum, and Marcia Hon Chapter 10 Detection of Abnormal Activities Stemming from Cognitive Decline Using Deep Learning Damla Arifoglu and Abdelhamid Bouchachia Chapter 11 Classification of Left Ventricular Hypertrophy and NAFLD through Decision Tree Algorithm Arnulfo González-Cantú, Maria Elena Romero-Ibarguengoitia, and Baidya Nath Saha Chapter 12 The Cutting Edge of Surgical Practice: Applications of Machine Learning to Neurosurgery Omar Khan, Jetan H. Badhiwala, Muhammad Ali Akbar, and Michael G. Fehlings Chapter 13 A Novel MRA-Based Framework for the Detection of Cerebrovascular Changes and Correlation to Blood Pressure Ingy El-Torgoman, Ahmed Soliman, Ali Mahmoud, Ahmed Shalaby, Mohamm ed Ghazal, Guruprasad Giridharan, Jasjit S. Suri, and Ayman El-Baz Chapter 14 Early Classification of Renal Rejection Types: A Deep Learning Approach Mohamed Shehata, Fahmi Khalifa, Ahmed Soliman, Shams Shaker, Ahmed Shalaby, Maryam El-Baz, Ali Mahmoud, Mohamed Abou El-Ghar, Mohammed Ghazal, Amy C. Dwyer, Jasjit S. Suri, and Ayman El-Baz Index
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2021
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 610.285; Medical informatics; Machine learning; Medicine -- Data processing
• Languages: English
• ISBNs: 9780429687334; 9781351588744; 9781315101323
• Related ISBNs: 9781138106901
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.