LEADER 04522nam 22006255 450 001 9910847579703321 005 20250807153221.0 010 $a3-031-53148-5 024 7 $a10.1007/978-3-031-53148-4 035 $a(MiAaPQ)EBC31260738 035 $a(Au-PeEL)EBL31260738 035 $a(CKB)31406592900041 035 $a(MiAaPQ)EBC31319609 035 $a(Au-PeEL)EBL31319609 035 $a(DE-He213)978-3-031-53148-4 035 $a(EXLCZ)9931406592900041 100 $a20240408d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAI and Neuro-Degenerative Diseases $eInsights and Solutions /$fedited by Loveleen Gaur, Ajith Abraham, Reuel Ajith 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (184 pages) 225 1 $aStudies in Computational Intelligence,$x1860-9503 ;$v1131 311 08$a3-031-53147-7 320 $aIncludes bibliographical references and index. 327 $a1. Demystifying: The Role of Artificial Intelligence in Neurodegenerative Diseases -- 2. Role Of Artificial Intelligence and Internet of Things in Neurodegenerative Diseases -- 3. Explainable Artificial Intelligence (XAI) on Neurogenerative Diseases -- 4. Clinical Genomics to Drug Discovery Using Machine Learning for Neurodegenerative disorders: A Future Perspective -- 5. Amyotrophic Lateral Sclerosis (ALS) Monitoring using Explainable AI -- 6. Prevalence of Dementia in India -- 7. Exploring AI's Role in Managing Neurodegenerative Disorders: Possibilities and Hurdles -- 8. Artificial Intelligence in Neuro Degenerative Diseases: Opportunities and Challenges -- 9. Ethical considerations: Case Scenarios. 330 $aThis book explores the current state of healthcare practice and provides a roadmap for harnessing artificial intelligence (AI) and other modern cognitive technologies for neurogenerative diseases. The main goal of this book is to look at how these techniques can be used to classify patients with neurodegenerative diseases by extracting data from multiple modalities. It demonstrates that the growing development of computer-aided diagnosis systems has a lot of potential to help with the diagnostic process. It offers an analysis of the prospective and perils in implementing such state of the art. Progressive brain disorders with a high prevalence in the general population include Parkinson's disease, Alzheimer's disease and other types of dementia, Huntington's disease, and motor neuron disease. Worldwide, it is estimated that 33 million people have Alzheimer's disease, and 10 million people have Parkinson's disease. The global health economy is significantly impacted by these disorders, which affect both the patient and the caregivers. Various diagnostic techniques are used for differential diagnoses, such as brain imaging, EEG analysis, molecular analysis, and cognitive, psychological, and physical examination. The book aims to develop effective treatments, enhance patient quality of life, and extend life expectancy. It focuses on novel artificial intelligence approaches to clarify the pathogenesis of neurodegenerative disorders and provide early diagnosis. The authors compile recent developments based on machine learning and deep learning techniques to diagnose neurodegenerative diseases using imaging, genetic, and clinical data. The authors support initiatives and methods that aim to improve the application of algorithms in diagnostic practice. 410 0$aStudies in Computational Intelligence,$x1860-9503 ;$v1131 606 $aComputational intelligence 606 $aBiomedical engineering 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aBiomedical Engineering and Bioengineering 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aBiomedical engineering. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aBiomedical Engineering and Bioengineering. 615 24$aArtificial Intelligence. 676 $a610.285 702 $aGaur$b Loveleen 702 $aAbraham$b Ajith$f1968- 702 $aAjith$b Reuel 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910847579703321 996 $aAI and Neuro-Degenerative Diseases$94266466 997 $aUNINA