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

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書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders影響因子(影響力)




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders影響因子(影響力)學(xué)科排名




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders網(wǎng)絡(luò)公開度




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders被引頻次




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders被引頻次學(xué)科排名




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders年度引用




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders年度引用學(xué)科排名




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders讀者反饋




書目名稱Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders讀者反饋學(xué)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..

手術(shù)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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