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AI-driven Alzheimer's disease detection and prediction

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	AI-driven Alzheimer's disease detection and prediction/ edited by Umesh Kumar Lilhore, Abhineet Anand, Abhishek Kumar, Satya Prakash Yadav, Narayan Vyas.
其他題名:	Artificial intelligence-driven Alzheimer's disease detection and prediction
其他作者:	Lilhore, Umesh Kumar,
出版者:	Hershey, Pennsylvania :IGI Global, : 2024.,
面頁冊數:	1 online resource (xvii, 441 p.)
標題:	Alzheimer's disease - Diagnosis. -
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-3605-2
ISBN:	9798369336069

AI-driven Alzheimer's disease detection and prediction
AI-driven Alzheimer's disease detection and prediction[electronic resource] /Artificial intelligence-driven Alzheimer's disease detection and predictionedited by Umesh Kumar Lilhore, Abhineet Anand, Abhishek Kumar, Satya Prakash Yadav, Narayan Vyas. - Hershey, Pennsylvania :IGI Global,2024. - 1 online resource (xvii, 441 p.)

Includes bibliographical references and index.

Chapter 1. Introduction to Alzheimer's disease, biomarkers, and the AI revolution -- Chapter 2. Neuroimaging and biomarkers in AD detection -- Chapter 3. Integrating AI in alzheimer's disease management: a strategic approach for healthcare administrators -- Chapter 4. Advanced deep learning approaches for Alzheimer's disease: enhancing diagnostic classification and prognostic prediction -- Chapter 5. Advancements in Alzheimer's diagnosis: a comprehensive exploration of AI-powered diagnostic tools and software -- Chapter 6. AI-powered paradigm shift: non-invasive biomarkers for early detection of Alzheimer's disease -- Chapter 7. AI-enhanced drug discovery for Alzheimer's -- Chapter 8. AI in neurodegeneration prediction: exploring advanced approaches for Alzheimer's disease progression -- Chapter 9. Strategic management of AI-enhanced Alzheimer's disease prediction models: navigating ethical and regulatory frontiers -- Chapter 10. Unravelling AI and machine learning essentials in Alzheimer's research -- Chapter 11. Revolutionizing Alzheimer's diagnosis: navigating the challenges and embracing opportunities in the clinical integration of AI-powered tools -- Chapter 12. Unravelling Alzheimer's: the AI revolution in diagnosis and prediction -- Chapter 13. Role of artificial intelligence in cognitive assessment and early detection of Alzheimer's disease -- Chapter 14. Unravelling data challenges in AI-driven Alzheimer's research -- Chapter 15. Unveiling Alzheimer's early signs: AI-driven insights through neuroimaging and biomarkers -- Chapter 16. Real-world impact: case studies and success stories in AI-driven Alzheimer's disease research and care -- Chapter 17. Patient-centered AI solutions for managing Alzheimer's disease -- Chapter 18. Navigating the administrative landscape of AI in Alzheimer's disease detection: a comprehensive management studies perspective -- Chapter 19. Machine learning models for Alzheimer's disease detection: an in-depth exploration, including deep learning approaches -- Chapter 20. Intelligent techniques for detection and diagnosis of neurodegenerative diseases -- Chapter 21. Integrating genomic data and genetic risk factors with AI for predicting susceptibility to Alzheimer's disease -- Chapter 22. Global initiatives and collaborations in AI for Alzheimer's disease -- Chapter 23. Challenges and future directions in AI-driven Alzheimer's disease research and care -- Chapter 24. Educating healthcare professionals on AI in Alzheimer's disease -- Chapter 25. Cognitive assessment and early detection of Alzheimer's disease: harnessing AI through tasks and games -- Chapter 26. Ethical and privacy considerations in AI-driven AD research -- Chapter 27. Exploring the role of natural learning processing in Alzheimer's disease research and prediction.

"This book is the culmination of our collaborative efforts, bringing together expertise from various disciplines, including artificial intelligence, computer science, neuroscience, and healthcare. Our shared goal is to address the pressing challenges posed by Alzheimer's disease through innovative AI-driven solutions"--

Mode of access: World Wide Web.

ISBN: 9798369336069Subjects--Topical Terms:

791236
Alzheimer's disease
--Diagnosis.Subjects--Index Terms:

Alzheimer's Disease.Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: RC523 / .A36155 2024eb

Dewey Class. No.: 616.8/311

National Library of Medicine Call No.: WM 220 / .A36155 2024eb

AI-driven Alzheimer's disease detection and prediction
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300 $a 1 online resource (xvii, 441 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Introduction to Alzheimer's disease, biomarkers, and the AI revolution -- Chapter 2. Neuroimaging and biomarkers in AD detection -- Chapter 3. Integrating AI in alzheimer's disease management: a strategic approach for healthcare administrators -- Chapter 4. Advanced deep learning approaches for Alzheimer's disease: enhancing diagnostic classification and prognostic prediction -- Chapter 5. Advancements in Alzheimer's diagnosis: a comprehensive exploration of AI-powered diagnostic tools and software -- Chapter 6. AI-powered paradigm shift: non-invasive biomarkers for early detection of Alzheimer's disease -- Chapter 7. AI-enhanced drug discovery for Alzheimer's -- Chapter 8. AI in neurodegeneration prediction: exploring advanced approaches for Alzheimer's disease progression -- Chapter 9. Strategic management of AI-enhanced Alzheimer's disease prediction models: navigating ethical and regulatory frontiers -- Chapter 10. Unravelling AI and machine learning essentials in Alzheimer's research -- Chapter 11. Revolutionizing Alzheimer's diagnosis: navigating the challenges and embracing opportunities in the clinical integration of AI-powered tools -- Chapter 12. Unravelling Alzheimer's: the AI revolution in diagnosis and prediction -- Chapter 13. Role of artificial intelligence in cognitive assessment and early detection of Alzheimer's disease -- Chapter 14. Unravelling data challenges in AI-driven Alzheimer's research -- Chapter 15. Unveiling Alzheimer's early signs: AI-driven insights through neuroimaging and biomarkers -- Chapter 16. Real-world impact: case studies and success stories in AI-driven Alzheimer's disease research and care -- Chapter 17. Patient-centered AI solutions for managing Alzheimer's disease -- Chapter 18. Navigating the administrative landscape of AI in Alzheimer's disease detection: a comprehensive management studies perspective -- Chapter 19. Machine learning models for Alzheimer's disease detection: an in-depth exploration, including deep learning approaches -- Chapter 20. Intelligent techniques for detection and diagnosis of neurodegenerative diseases -- Chapter 21. Integrating genomic data and genetic risk factors with AI for predicting susceptibility to Alzheimer's disease -- Chapter 22. Global initiatives and collaborations in AI for Alzheimer's disease -- Chapter 23. Challenges and future directions in AI-driven Alzheimer's disease research and care -- Chapter 24. Educating healthcare professionals on AI in Alzheimer's disease -- Chapter 25. Cognitive assessment and early detection of Alzheimer's disease: harnessing AI through tasks and games -- Chapter 26. Ethical and privacy considerations in AI-driven AD research -- Chapter 27. Exploring the role of natural learning processing in Alzheimer's disease research and prediction.
520 3 $a "This book is the culmination of our collaborative efforts, bringing together expertise from various disciplines, including artificial intelligence, computer science, neuroscience, and healthcare. Our shared goal is to address the pressing challenges posed by Alzheimer's disease through innovative AI-driven solutions"-- $c Provided by publisher.
538 $a Mode of access: World Wide Web.
650 0 $a Alzheimer's disease $x Diagnosis. $3 791236
650 0 $a Alzheimer's disease $x Diagnosis $x Data processing. $3 1498707
650 0 $a Alzheimer's disease $x Treatment. $3 791237
650 0 $a Alzheimer's disease $x Treatment $x Data processing. $3 1498708
650 0 $a Artificial intelligence $x Medical applications. $3 600038
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650 2 $a Alzheimer's Disease $x therapy. $3 1498710
650 2 $a Artificial Intelligence. $3 646849
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653 $a Alzheimer's Disease.
653 $a Artificial Intelligence.
653 $a Biomarkers.
653 $a Clinical Integration.
653 $a Cognitive Assessment.
653 $a Data Collection.
653 $a Drug Discovery.
653 $a Ethical Considerations.
653 $a Genetic Risk Factors.
653 $a Global Initiatives.
653 $a Machine Learning.
653 $a Neurodegeneration Prediction.
653 $a Neuroimaging.
653 $a Patient-Centered Solutions.
653 $a Privacy Considerations.
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700 1 $a Lilhore, Umesh Kumar, $d 1982- $3 1458815
700 1 $a Anand, Abhineet, $d 1975- $3 1458805
700 1 $a Kumar, Abhishek, $d 1989- $3 1458804
700 1 $a Yadav, Satya Prakash. $e editor. $1 https://orcid.org/0000-0002-2634-5600 $3 1401850
700 1 $a Vyas, Narayan, $d 1998- $3 1458811
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