東華大學圖書館 |

AI-driven Alzheimer's disease detection and prediction

Record Type:	Electronic resources : Monograph/item
Title/Author:	AI-driven Alzheimer's disease detection and prediction/ edited by Umesh Kumar Lilhore, Abhineet Anand, Abhishek Kumar, Satya Prakash Yadav, Narayan Vyas.
remainder title:	Artificial intelligence-driven Alzheimer's disease detection and prediction
other author:	Lilhore, Umesh Kumar,
Published:	Hershey, Pennsylvania :IGI Global, : 2024.,
Description:	1 online resource (xvii, 441 p.)
[NT 15003449]:	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.
Subject:	Alzheimer's disease - Diagnosis. -
Online resource:	https://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:

665807
Alzheimer's disease
--Diagnosis.Subjects--Index Terms:

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

542853
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
LDR:04983nmm a2200505 a 4500 001 2415574
006 m o d
007 cr nn |||muauu
008 260207s2024 pau ob 001 0 eng d
020 $a 9798369336069 $q (ebook)
020 $z 9798369366370 $q (softcover)
020 $z 9798369336052 $q (hardback)
035 $a (CaBNVSL)slc00006594
035 $a (OCoLC)1452412682
035 $a 00336533
040 $a CaBNVSL $b eng $c CaBNVSL $d CaBNVSL
041 0 $a eng
050 4 $a RC523 $b .A36155 2024eb
060 0 0 $a WM 220 $b .A36155 2024eb
082 0 4 $a 616.8/311 $2 23
245 0 0 $a AI-driven Alzheimer's disease detection and prediction $h [electronic resource] / $c edited by Umesh Kumar Lilhore, Abhineet Anand, Abhishek Kumar, Satya Prakash Yadav, Narayan Vyas.
246 3 $a Artificial intelligence-driven Alzheimer's disease detection and prediction
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2024.
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 665807
650 0 $a Alzheimer's disease $x Diagnosis $x Data processing. $3 3793439
650 0 $a Alzheimer's disease $x Treatment. $3 660535
650 0 $a Alzheimer's disease $x Treatment $x Data processing. $3 3793440
650 0 $a Artificial intelligence $x Medical applications. $3 900591
650 2 $a Alzheimer's Disease $x diagnosis. $3 3793441
650 2 $a Alzheimer's Disease $x therapy. $3 3793442
650 2 $a Artificial Intelligence. $3 769149
650 2 $a Electronic Data Processing. $3 3508750
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.
655 4 $a Electronic books. $2 lcsh $3 542853
700 1 $a Lilhore, Umesh Kumar, $d 1982- $3 3730082
700 1 $a Anand, Abhineet, $d 1975- $3 3730072
700 1 $a Kumar, Abhishek, $d 1989- $3 3730071
700 1 $a Yadav, Satya Prakash. $3 3593152
700 1 $a Vyas, Narayan, $d 1998- $3 3730078
710 2 $a IGI Global. $3 1361470
776 0 $c (Original) $w (DLC)2024034892
776 0 8 $i Print version: $z 9798369336052 $w (DLC) 2024034892
856 4 0 $u https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-3605-2