000			03066nam a22003377a 4500
003			OSt
005			20250618155008.0
008			250618b |||||||| |||| 00| 0 eng d
020			_a9783031531477 _q(hardcover)
040			_beng _cDLC _dDLC _erda _aSai University Library
082			_223 _a616.83 _bGAU
245	0	0	_aAI and Neuro-Degenerative Diseases : _bInsights and Solutions / _cLoveleen Gaur, Ajith Abraham, Ruel Ajith, editors
260			_aCham : _bSpringer _c[2024]
264		1	_aCham : _bSpringer _c[2024] _c©2024
300			_avi, 181 pages : _billustrations
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
490	1		_aStudies in computational intelligence ; _vVolume 1131
504			_aIncludes bibliographical references
520			_aThis 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
650		0	_aNervous system _xDegeneration _xData processing
650		0	_aArtificial intelligence _xMedical applications
650			_aExpert systems (Computer science)
700	1		_aGaur, Loveleen _eeditor
700	1		_aAbraham, Ajith _eeditor
700			_aAjith, Reuel _eeditor
830		0	_aStudies in computational intelligence ; _vVolume 1131
856			_3Table of Contents only _uhttps://link.springer.com/book/10.1007/978-3-031-53148-4#toc
942			_2ddc _cBK
999			_c6785 _d6785