Table of Contents
Part I: Introduction and Challenges
1. Introduction to Neurological Disorders
T. Manonmani, Mohit Malik, P. Abinaya
2. Navigating the Complexities of the Brain: Challenges and Opportunities in Computational Neurology
Ginni Arora, Alvaro Rocha, and Syamsundar Patta
3. Challenges and Opportunities in Computational Neurology
S. Vijayanand and C. Priya
4. Ethical Issues in Neurodisorder Diagnosis
Rufina Hussain, Safdar Tanweer, Sameena Naaz, and Sherin Zafar
5. Ethical Issues in Neurodisorder Diagnosis: Computational Intelligence toward Compassionate Psychiatric Treatment
Bhupinder Singh, Rishabha Malviya, and Christian Kaunert
Part II: Neuroimaging and Diagnostic Techniques
6. Improving Magnetic Resonance Imaging (MRI) for Better Understanding of Neurological Disorders
Mohd Abdullah Siddiqui, Sohrab A. Khan, Charu Chhabra, Sahar Zaidi, and Habiba Sundus
7. Advancements in Neuroimaging Techniques in Encephalopathy
Firdaus Jawed, Rabia Aziz, Sohrab Ahmad Khan, Sumbul Ansari, and Shahnawaz Answer
8. Targeted Drug Delivery for Neurological Disorders
Bhupen Kalita
9. Intelligent Deep Learning Algorithms for Autism Spectrum Disorder Diagnosis
V. Thamilarasi, R. Roselin, P. Pushpa, M. Kannan, and B. P. Sreejith Vignesh
10. Advanced Neuroimaging with Generative Adversarial Networks
Basil Hanafi, Mohammad Ubaidullah Bokhari, and Imran Khan
11. Machine Learning Strategy with Decision Trees for Parkinson's Detection by Analyzing the Energy of the Acoustic Data
Arun P, Enrico M. Staderini, Madhukumar S, Careena P, Sarath P V, and Sreesh P R
12. Adaptive Convolution Neural Network-Based Brain Tumor Detection from MR Images
C. Prajitha, K. Thamaraiselvi, Rinesh. S, K. P. Sridhar, and Abubeker K M
13. STN-DRN: Integrating Spatial Transformer Network with Deep Residual Network for Multiclass Classification of Alzheimer’s Disease
Prabu Selvam, Sudharson S, and Senthil Prakash PN
Part III: Machine Learning & AI Applications in Neurological Disorders
14. Evaluation of Supervised Learning Algorithms in Detection of Neurodisorders: A Focus on Parkinson's Disease
Chitigala Mouleeshwari, Kishor Kumar Reddy C, Manoj Kumar Reddy, and Srinath Doss
15. Comparative Analysis of Supervised and Unsupervised Learning Algorithms in the Detection of Alzheimer’s Disease
Binson V A, Starlet Ben Alex, and Rangith Kuriakose
16. Deep Learning Techniques in Neurological Disorder Detection
Manisha Nagar, Shikha Singh, Sanjay Singh, and Ruchi Jain
17. From Data to Diagnosis: Supervised Learning's Impact on Neurodisorder Detection, with a focus on Autism Spectrum Disorder
S.Srividhya and S.R.Lavanya
18. Parkinson's Disease Detection from Drawing Images using Deep Pretrained Models
Sourabh Shastri, Sachin Kumar, and Vibhakar Mansotra
19. Optimizing Digital Healthcare for Alzheimer's Disease: A Deep Federated Learning Convolutional Neural Network Scheme (DFLCNNS)
Swathi Sambangi , T Kusuma , D Srinivasa Rao , G Lakshmeshwari , and Rakhee
20. Artificial Intelligence: A Game-Changer in Parkinson’s Disease Neurorehabilitation
Nabeela Rehman, Arshya Anwar, and Sahar Zaidi
21. Targeting Upper-Limb Sensory Gaps: New Rehab Insights for Chronic Neck Pain
Sahar Zaidi, Sohrab Ahmad Khan, Charu Chhabra, Habiba Sundus, and Irshad Ahmad
Editor(s)
Biography
S. N. Kumar received his B.E. degree from the Department of Electrical and Electronics Engineering, Sun College of Engineering and Technology, in 2007, his M.E. degree in applied electronics from the Anna University of Technology, Tirunelveli, and his Ph.D. degree from the Sathyabama Institute of Science and Technology in 2019. He is currently an Associate Professor with the Department of Electrical and Electronics Engineering, Amal Jyothi College of Engineering, Kanjirappally, and his research areas include medical image processing and embedded systems.
Sherin Zafar is an Assistant Professor of Computer Science and Engineering at the School of Engineering Sciences and Technology, Jamia Hamdard University, with a decade of successful experience in teaching and research management. She specializes in wireless networks, soft computing, and network security.
Sameena Naaz is a Senior Lecturer at the Department of Computer Science, School of Arts, Humanities and Social Sciences at the University of Roehampton, London, UK, with more than 22 years of experience. She received her M.Tech. degree in Electronics with Specialization in Communication and Information Systems from Aligarh Muslim University in 2000 and completed her Ph.D. from Jamia Hamdard in the field of distributed systems in 2014. Her research interests include distributed systems, cloud computing, big data, machine learning, data mining, and image processing.
