Titlebook: Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders; M. Murugappan,Yuvaraj Rajamanickam Book 2022 The Editor(s) (

Coronary-Artery

书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders影响因子(影响力)




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders影响因子(影响力)学科排名




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders网络公开度




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders网络公开度学科排名




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders被引频次




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders被引频次学科排名




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders年度引用




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders年度引用学科排名




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders读者反馈




书目名称Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders读者反馈学科排名

Arthropathy

Book 2022a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced

改良

Book 2022t explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders..

手术刀

M. Murugappan,Yuvaraj RajamanickamPresents the concepts of CAD for various neurological disorders;.Covers biomedical signal processing and machine learning/deep learning techniques;.Includes case studies, real-time examples, and resea

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erythema

978-3-030-97847-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

MAOIS

https://doi.org/10.1007/978-81-322-1976-7phalogram (EEG). Identifying an abnormal EEG serves as a preliminary indicator before specialized testing to determine the neurological disorder. Traditional identification methods involve manual perusal of the EEG signals. This method is relatively slow and tedious, requires trained neurologists, a

Modicum

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