| Description |
1 online resource (184 p.) |
| Series |
Studies in Computational Intelligence Series ; v.1131 |
|
Studies in Computational Intelligence Series
|
| Contents |
Intro -- Contents -- Demystifying the Role of Artificial Intelligence in Neurodegenerative Diseases -- 1 Introduction -- 2 Literature Review -- 3 The Transformative Role of AI in Healthcare -- 3.1 AI in Disease Detection -- 3.2 AI in Disease Diagnosis -- 3.3 AI in Disease Management -- 4 Early Detection and Diagnosis of Neurodegenerative Diseases Using AI -- 4.1 Information Procurement and Preprocessing -- 4.2 Imaging Analysis -- 4.3 Biomarkers Identification -- 4.4 Prescient Modeling -- 4.5 Computerized Biomarkers and Wearable Gadgets -- 4.6 Decision Support Systems -- 5 Image Analysis |
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6 The Role of Artificial Intelligence in Drug Discovery for Neurodegenerative Diseases -- 6.1 Data Mining and Analysis -- 6.2 Predictive Model -- 6.3 Virtual Screening and Drug Design -- 6.4 Reusing Existing Drugs -- 6.5 Explore Biomarkers -- 6.6 Clinical Trial Optimization -- 6.7 Collaboration and Knowledge Sharing -- 7 Personalized Medicine for Patients with Neurodegenerative Diseases -- 7.1 Risk Assessment and Prediction Model -- 7.2 Accurate Diagnosis -- 7.3 Prognosis of Response to Treatment -- 7.4 Drug Selection and Optimization -- 7.5 Continuous Monitoring and Remote Care |
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7.6 Treatment Adjustment and Decision Support -- 7.7 Patient Empowerment and Education -- 8 Controlling Diseases Progression and Prediction -- 8.1 Disease Progression Pattern -- 8.2 Early Detection and Risk Assessment -- 8.3 Prognosis of Response to Treatment -- 8.4 Adaptive Treatment Strategies -- 8.5 Prognostic Tool -- 8.6 Personal Disease Management -- 9 Remote Monitoring and Supporting Tools for Healthcare Providers -- 9.1 Remote Patient Monitoring -- 9.2 Predictive Analytics -- 9.3 Remote and Virtual Consultation -- 9.4 Decision Support System -- 9.5 Data Analysis and Clinical Insights |
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9.6 Care Coordination and Patient Management -- 10 Artificial Intelligence in Alzheimer's Disease -- 11 Machine Learning Algorithms -- 12 Deep Learning Models -- 13 Natural Language Processing (NLP) Models -- 14 Generative Adversarial Networks (GANs) Models -- 15 Reinforcement Learning (Rl) Models -- 16 Conclusion -- 17 Future Scope -- References -- Role of Artificial Intelligence and Internet of Things in Neurodegenerative Diseases -- 1 Introduction -- 2 Literature Review -- 3 Rate of Cases of Neurodegenerative Diseases -- 4 Impact of AI on Neurodegenerative Diseases |
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5 Impact of IoT on Neurodegenerative Diseases -- 6 Integration of IoT with AI in the Context of Neurodegenerative Diseases -- 6.1 Remote Monitoring and Telemedicine -- 6.2 Predictive Analytics and Early Intervention -- 6.3 Personalized Rehabilitation and Therapy -- 6.4 Data-Driven Research and Drug Development -- 6.5 Caregiver Support and Assistance -- 6.6 Population Health Management -- 7 AI Algorithms on Neurodegenerative Diseases -- 8 Potential of AI in the Field of Neurodegenerative Diseases -- 9 The Role of IoT in Neurodegenerative Diseases |
| Summary |
This book explores the current state of healthcare practice and provides a roadmap for harnessing artificial intelligence (AI) and other modern cognitive technologies for neurogenerative diseases. The main goal of this book is to look at how these techniques can be used to classify patients with neurodegenerative diseases by extracting data from multiple modalities. It demonstrates that the growing development of computer-aided diagnosis systems has a lot of potential to help with the diagnostic process. It offers an analysis of the prospective and perils in implementing such state of the art. Progressive brain disorders with a high prevalence in the general population include Parkinson's disease, Alzheimer's disease and other types of dementia, Huntington's disease, and motor neuron disease. Worldwide, it is estimated that 33 million people have Alzheimer's disease, and 10 million people have Parkinson's disease. The global health economy is significantly impacted by these disorders, which affect both the patient and the caregivers. Various diagnostic techniques are used for differential diagnoses, such as brain imaging, EEG analysis, molecular analysis, and cognitive, psychological, and physical examination. The book aims to develop effective treatments, enhance patient quality of life, and extend life expectancy. It focuses on novel artificial intelligence approaches to clarify the pathogenesis of neurodegenerative disorders and provide early diagnosis. The authors compile recent developments based on machine learning and deep learning techniques to diagnose neurodegenerative diseases using imaging, genetic, and clinical data. The authors support initiatives and methods that aim to improve the application of algorithms in diagnostic practice |
| Notes |
Description based upon print version of record |
|
10 Ai and IoT Based Models Necessary for Neurodegenerative Diseases |
| Subject |
Nervous system -- Degeneration -- Data processing
|
|
Artificial intelligence -- Medical applications.
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| Form |
Electronic book
|
| Author |
Abraham, Ajith
|
|
Ajith, Reuel
|
| ISBN |
9783031531484 |
|
3031531485 |
|
