Artificial Intelligence and Machine Learning in Neurology, 2 Volume Set

1. Auflage 2026
ISBN: 978-1-394-38910-0
Verlag: John Wiley & Sons Inc

Buch, Englisch, 1072 Seiten

Unlock the future of brain health with this indispensable guide, which offers a comprehensive exploration of how artificial intelligence and machine learning are revolutionizing the diagnosis, treatment, and management of complex neurological disorders.

As neurology grapples with some of the most challenging and pervasive health issues of our time, such as Alzheimers, Parkinsons, and stroke, AI offers the potential to transcend traditional barriers in treatment and management. Technologies such as machine learning models, neural networks, and cognitive computing are used to better understand and simulate brain functions, offering insights that are impossible for traditional analytical methods. Artificial Intelligence and Machine Learning in Neurology explores the pioneering intersection of neuroscience and artificial intelligence, offering a comprehensive examination of how machine learning and AI technologies are revolutionizing the fields of neurology and mental health. This book delves into cutting-edge research and practical applications of AI in diagnosing, treating, and managing neurological disorders. It discusses the development of intelligent diagnostic systems, personalized medicine approaches, and the potential of AI to analyze vast amounts of neurological data for insights. Additionally, the book addresses ethical considerations, challenges, and future prospects in the integration of AI into neurohealth sciences, making it an indispensable guide to this emerging technology.

Autoren/Hrsg.

Pandey, Abhishek Kumar

Kumar, Abhishek

Manuja, Manoj

Singh Rathore, Pramod

Ahuja, Sachin

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Neurobiologie, Verhaltensbiologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Neurowissenschaften, Kognitionswissenschaft

Inhaltsverzeichnis

Brief Contents of Volume 1

Preface

1 Ethical Frameworks for AI-Driven Healthcare: Genetic and Epidemiological Perspectives on Ethical AI Frameworks 1
Kailas D. Datkhile and Milind Pande

2 Ethical Challenges and Guidelines for AI Deployment in Healthcare: Urological and Gastroenterological Perspectives on Ethical AI Deployment 25
Abhijeet R. Katkar and U. P. Waghe

3 Bias Mitigation and Fairness in AI Healthcare Applications: Addressing Bias and Equity in AI-Driven Healthcare Solutions 47
Dhanaji Wagh and Prashant S. Jadhav

4 Regulatory Compliance and Data Governance in AI-Driven Healthcare: Legal and Regulatory Considerations for AI-Driven Healthcare Solutions 79
Rahul S.S. and Satish V. Kakade

5 Ensuring Responsible Data Use in Healthcare AI Applications: Radiological and Surgical Approaches to Responsible AI Data Usage 109
Asif Tamboli and Kalpana Malpe

6 Implementing Secure Health Data Exchange with Blockchain: Orthopedic and Ophthalmological Insights into Secure Health Data Exchange 129
Patil Nitin S. and Mahendra Alate

7 Securing Clinical Trial Data with Decentralized Technologies and Exploring Blockchain Applications in Modern Healthcare Management 153
Patange Aparna P. and Kadam Shrikant Rangrao

8 Blockchain-Enabled Healthcare Ecosystems: Scalability, Security, and Interoperability 177
Mario Antony and Trupti S. Bhosale

9 Advanced Threat Detection in Health Information Systems with Cybersecurity Technologies in Modern Healthcare Applications 215
Shantanu Kulkarni and Shinde Patil Girisha Suresh

10 Interoperability and Standardization in Healthcare System Integration: Interfacing Wearable Devices with Electronic Health Records 243
Nikhilchandra Mahajan and Kalpana Malpe

11 Fundamentals of Predictive Analytics in Healthcare: Nephrological and Pulmonological Fundamentals of Predictive Analytics 283
Patil Dilip P. and Rasika Chafle

12 Advanced Techniques in Predictive Analytics: Ensemble Methods and Feature Engineering for Healthcare Predictions 315
Nelson Nishant Kumar Lyngdoh and Dheeraj Mane

13 Leveraging Machine Learning for Predictive Healthcare Models: Hematological and Rheumatologic Approaches to Machine Learning in Healthcare 351
Hemchandra V. Nerlekar and Prashant S. Jadhav

14 AI-Driven Risk Assessment Models for Proactive Glaucoma Monitoring 375
Abhay D. Havle and Kalpana Malpe

15 Next-Generation AI/ML Algorithms for Health Monitoring: Deep Learning and Neural Network Architectures 397
Satish V. Kakade and Shyamala Moantri

16 AI-Driven Personalized Care for Chronic Disease Patients Tailoring Treatments and Interventions Using AI for Conditions Such as Diabetes, Hypertension, and Heart Disease 437
S. T. Thorat and Fazil Sheikh

17 AI in Diabetes Management: Personalized Insulin Dosing and Glucose Monitoring Innovations in Diabetes Care Through AI for Continuous Glucose Monitoring and Insulin Therapy Optimization 459
Gauri Tamhankar and Kalpana Malpe

18 Chronic Heart Disease Management with AI: Predictive Models and Early Interventions Using AI to Monitor Heart Disease Patients, Predict Adverse Events, and Recommend Preventive Measures 483
Patil Dilip P. and Swapna Kamble

Brief Contents of Volume 2

19 AI-Assisted Decision Support Systems in Chronic Disease Treatment: The Role of AI in Assisting Clinicians with Diagnosis, Treatment Recommendations, and Patient Management 507

20 Introduction to AI in Chronic Disease Management Overview of AI Technologies and Their Transformative Impact on Chronic Disease Care 533

21 Artificial Intelligence–Driven Identification of Biomarkers for Precision Medicine Advancements Through Bioinformatics in Healthcare Applications 555

22 Real-Time Chronic Disease Management with Smart Devices Integrating Internet-of-Things Technology in Healthcare Applications 581

23 Future Trends in Wearable Healthcare Technology: Innovations and Emerging Technologies in Wearable Devices 609

24 Challenges and Opportunities in Real-Time Data Processing: Advancements and Limitations in Real-Time Data Analytics 647

25 Overview of AI and Machine Learning Algorithms in Health Monitoring: Dermatological and Infectious Disease Applications of AI in Health Monitoring 685

26 Machine Learning Algorithms in Early Detection of Chronic Diseases Applications of Supervised and Unsupervised Learning for Early Diagnosis and Risk Prediction 711

27 Intelligent Neurohealth Systems: Revolutionizing Diagnosis and Therapy 741

28 Cognitive Computing and Neurobiology: A New Era in Brain Health 763

29 Natural Language Processing (NLP) in Chronic Disease Management Utilizing NLP to Extract Critical Information from Medical Records for Improving Chronic Disease Care 785

30 Remote Monitoring and Telehealth Solutions for Chronic Disease Care Integration of AI in Telemedicine for Continuous Patient Monitoring and Real-Time Interventions 811

31 Innovative Approaches in Mental Health Intervention Using Wearable Devices: Novel Therapeutic Modalities and Interventions 833

32 Artificial Intelligence Driven Identification of Biomarkers for Precision Medicine Advancements Through Bioinformatics in Healthcare Applications 869

33 Future Directions and Opportunities in AI-Driven Healthcare: Family Medicine and Anesthesiology Future Directions in AI-Driven Healthcare 895

34 Future Directions in AI-Powered Medical Diagnostics: Innovations and Challenges in AI-Driven Diagnostic Technologies 917

35 AI in Cancer Screening and Early Detection 955

36 The Rhizobium-Legume Symbiosis and Biofortification in Sustainable Agriculture 975

Über Autor(innen)

Abhishek Kumar, PhD is an Assistant Professor and the Associate Director of the Computer Science and Engineering Department at Chandigarh University with more than 13 years of experience. He has authored seven books, edited more than 50 books, and published more than 170 publications in reputed national and international journals, books, and conferences. His areas of interest include artificial intelligence, renewable energy image processing, computer vision, data mining, and machine learning.

Pramod Singh Rathore, PhD is an Assistant Professor in the Department of Computer and Communication Engineering at Manipal University with over 12 years of academic experience. He has published more than 85 papers in peer-reviewed national and international journals, books, and conferences, as well as numerous books. His research interests include computer networks, mining, and database management systems.

Sachin Ahuja, PhD is a Professor and Executive Director in the Department of Computer Science and Engineering at Chandigarh University. He has successfully led several funded projects in advanced areas like artificial intelligence, machine learning, and data mining, driving innovation and practical solutions. He has contributed to numerous high-quality academic books and served as a guest editor for special issues in reputed international journals.

Manoj Manuja, PhD is the Founder and CEO of Mystik Minds, a company dedicated to providing no-code AI education to students across diverse domains. Under his leadership, Mystik Minds has become a catalyst for empowering students from various backgrounds with essential AI skills, fostering inclusivity in technology education. He has hands-on expertise navigating the dynamic landscape of AI education, creating innovative and accessible learning pathways that resonate with learners from diverse fields.