LEADER 05873nam 22007815 450 001 996546828003316 005 20230531074505.0 010 $a981-9921-54-6 024 7 $a10.1007/978-981-99-2154-6 035 $a(MiAaPQ)EBC30558412 035 $a(Au-PeEL)EBL30558412 035 $a(OCoLC)1381094019 035 $a(DE-He213)978-981-99-2154-6 035 $a(BIP)089944693 035 $a(PPN)270613080 035 $a(EXLCZ)9926816413600041 100 $a20230531d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Analysis for Neurodegenerative Disorders$b[electronic resource] /$fedited by Deepika Koundal, Deepak Kumar Jain, Yanhui Guo, Amira S. Ashour, Atef Zaguia 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (267 pages) 225 1 $aCognitive Technologies,$x2197-6635 311 08$aPrint version: Koundal, Deepika Data Analysis for Neurodegenerative Disorders Singapore : Springer Singapore Pte. Limited,c2023 9789819921539 327 $aChapter 1. Introduction to neurodegenerative disorders -- Chapter 2. Neurodegenerative Disorders and available therapies: A review -- Chapter 3. Role of peptides in Neurodegenerative disorders by using Machine Learning techniques -- Chapter 4. Deep learning based classification of neurodegenerative disorders -- Chapter 5. EEG Processing and Machine Learning based Categorization of Epilepsy -- Chapter 6. An Automatic Edge-Region Based Level set Method for MRI Brain Image Segmentation -- Chapter 7. Multimodal Medical Image Fusion for identification of Neurodegenerative disorders Using Neutrosophic CNN Technique -- Chapter 8. Automated EEG temporal lobe signal processing for diagnosis of Alzheimer disease -- Chapter 9. Alzheimer Disease Identification based on the EEG Processing and Machine Learning -- Chapter 10. Deep Learning Models for Automatic Classification and Prediction of Alzheimer?s Disease -- Chapter 11. Machine learning models for Alzheimer Disease Detection using medical images -- Chapter 12. Transfer learning for precise classification of Parkinson disease from EEG signals -- Chapter 13. Analysis of Convolutional Neural Network Based Architecture for Parkinson -- Chapter 14. Challenges and Possible research directions. 330 $aThis book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders. This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: ? Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. ? Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. ? Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used. 410 0$aCognitive Technologies,$x2197-6635 606 $aMedical informatics 606 $aImage processing?Digital techniques 606 $aComputer vision 606 $aImage processing 606 $aMachine learning 606 $aArtificial intelligence?Data processing 606 $aHealth Informatics 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aImage Processing 606 $aMachine Learning 606 $aData Science 610 $aInternal Medicine 610 $aMedical 615 0$aMedical informatics. 615 0$aImage processing?Digital techniques. 615 0$aComputer vision. 615 0$aImage processing. 615 0$aMachine learning. 615 0$aArtificial intelligence?Data processing. 615 14$aHealth Informatics. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aImage Processing. 615 24$aMachine Learning. 615 24$aData Science. 676 $a616.800285 700 $aKoundal$b Deepika$01348025 701 $aJain$b Deepak Kumar$01365699 701 $aGuo$b Yanhui$01365700 701 $aAshour$b Amira S$01365701 701 $aZaguia$b Atef$01365702 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996546828003316 996 $aData Analysis for Neurodegenerative Disorders$93387850 997 $aUNISA