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Deep learning approaches for early d...

Bekal, Sreelekshmi, (1991-)

Deep learning approaches for early diagnosis of neurodegenerative diseases

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep learning approaches for early diagnosis of neurodegenerative diseasesRaul Villamarin Rodriguez, Hemachandran Kannan, Revathi T., Khalid Shaikh, Sreelekshmi Bekal, editors.
其他作者:	T., Revathi,
出版者:	Hershey, Pennsylvania :IGI Global,2024.
面頁冊數:	1 online resource (325 p.)
標題:	Deep learning (Machine learning)
電子資源:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1281-0
ISBN:	9798369312827$q(ebook)

Deep learning approaches for early diagnosis of neurodegenerative diseases
Deep learning approaches for early diagnosis of neurodegenerative diseases[electronic resource] /Raul Villamarin Rodriguez, Hemachandran Kannan, Revathi T., Khalid Shaikh, Sreelekshmi Bekal, editors. - Hershey, Pennsylvania :IGI Global,2024. - 1 online resource (325 p.)

Includes bibliographical references and index.

Chapter 1. Fundamentals of deep learning -- Chapter 2. Introduction to neurodegenerative diseases -- Chapter 3. Human brain imaging for cognitive neuroscience: data acquisition and preprocessing -- Chapter 4. A comprehensive survey of deep learning approaches in neurodegenerative disease diagnosis and prediction: deep learning techniques for neurodegenerative diseases -- Chapter 5. Deep learning techniques for Alzheimer's disease detection: a comprehensive study -- Chapter 6. Deep neural networks for early diagnosis of neurodegenerative diseases -- Chapter 7. Deep learning approaches in the early diagnosis of Parkinson's disease -- Chapter 8. Automated neurological brain disease detection in magnetic resonance imaging using deep learning approaches -- Chapter 9. Automatic diagnosis of Parkinson's disease based on deep learning models and multimodal data -- Chapter 10. Advancements in healthcare: harnessing machine learning for medical devices -- Chapter 11. Ethical considerations and challenges in neurodegenerative diseases using machine learning -- Chapter 12. Future directions and emerging trends.

" Within the context of global health challenges posed by intractable neurodegenerative diseases like Alzheimer's and Parkinson's, the significance of early diagnosis is critical for effective intervention, and scientists continue to discover new methods of detection. However, actual diagnosis goes beyond detection to include a significant analysis of combined data for many cases, which presents a challenge of several complicated calculations. Deep Learning Approachesfor Early Diagnosis of Neurodegenerative Diseases stands as a groundbreaking work at the intersection of artificial intelligence and neuroscience. The book orchestrates a symphony of cutting-edge techniques and progressions in early detection by assembling eminent experts from the domains of deep learning and neurology. Through a harmonious blend of research areas and pragmatic applications, this monumental work charts the transformative course to revolutionize the landscapeof early diagnosis and management of neurodegenerative disorders.Within the pages, readers will embark through the intricate landscape of neurodegenerative diseases, the fundamental underpinnings of deep learning, the nuances of neuroimagingdata acquisition and preprocessing, the alchemy of feature extraction and representation learning, and the symphony of deep learning models tailored for neurodegenerative disease diagnosis. The book also delves into integrating multimodal data to augment diagnosis, the imperative of rigorously evaluating and validating deep learning models, and the ethical considerations and challenges entwined with deep learning for neurodegenerative diseases."--

ISBN: 9798369312827$q(ebook)Subjects--Topical Terms:

913129
Deep learning (Machine learning)
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: RC376.5 / .D44 2024e

Dewey Class. No.: 616.8/3

National Library of Medicine Call No.: WL 358.5 / .D44 2024e

Deep learning approaches for early diagnosis of neurodegenerative diseases
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245 0 0 $a Deep learning approaches for early diagnosis of neurodegenerative diseases $h [electronic resource] / $c Raul Villamarin Rodriguez, Hemachandran Kannan, Revathi T., Khalid Shaikh, Sreelekshmi Bekal, editors.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2024.
300 $a 1 online resource (325 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Fundamentals of deep learning -- Chapter 2. Introduction to neurodegenerative diseases -- Chapter 3. Human brain imaging for cognitive neuroscience: data acquisition and preprocessing -- Chapter 4. A comprehensive survey of deep learning approaches in neurodegenerative disease diagnosis and prediction: deep learning techniques for neurodegenerative diseases -- Chapter 5. Deep learning techniques for Alzheimer's disease detection: a comprehensive study -- Chapter 6. Deep neural networks for early diagnosis of neurodegenerative diseases -- Chapter 7. Deep learning approaches in the early diagnosis of Parkinson's disease -- Chapter 8. Automated neurological brain disease detection in magnetic resonance imaging using deep learning approaches -- Chapter 9. Automatic diagnosis of Parkinson's disease based on deep learning models and multimodal data -- Chapter 10. Advancements in healthcare: harnessing machine learning for medical devices -- Chapter 11. Ethical considerations and challenges in neurodegenerative diseases using machine learning -- Chapter 12. Future directions and emerging trends.
520 3 $a " Within the context of global health challenges posed by intractable neurodegenerative diseases like Alzheimer's and Parkinson's, the significance of early diagnosis is critical for effective intervention, and scientists continue to discover new methods of detection. However, actual diagnosis goes beyond detection to include a significant analysis of combined data for many cases, which presents a challenge of several complicated calculations. Deep Learning Approachesfor Early Diagnosis of Neurodegenerative Diseases stands as a groundbreaking work at the intersection of artificial intelligence and neuroscience. The book orchestrates a symphony of cutting-edge techniques and progressions in early detection by assembling eminent experts from the domains of deep learning and neurology. Through a harmonious blend of research areas and pragmatic applications, this monumental work charts the transformative course to revolutionize the landscapeof early diagnosis and management of neurodegenerative disorders.Within the pages, readers will embark through the intricate landscape of neurodegenerative diseases, the fundamental underpinnings of deep learning, the nuances of neuroimagingdata acquisition and preprocessing, the alchemy of feature extraction and representation learning, and the symphony of deep learning models tailored for neurodegenerative disease diagnosis. The book also delves into integrating multimodal data to augment diagnosis, the imperative of rigorously evaluating and validating deep learning models, and the ethical considerations and challenges entwined with deep learning for neurodegenerative diseases."-- $c Provided by publisher.
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650 0 $a Nervous system $x Degeneration. $3 195201
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650 2 $a Deep Learning. $3 927365
650 2 $a Early Diagnosis. $3 374209
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700 1 $a T., Revathi, $q (Theerthagiri) $d 1989- $3 974220
700 1 $a Shaikh, Khalid $c (Of Prognica Labs). $3 974221
700 1 $a Bekal, Sreelekshmi, $d 1991- $3 974222
700 1 $a Kannan, Hemachandran, $d 1985- $3 974173
700 1 $a Rodriguez, Raul Villamarin. $3 974174
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