Present book discusses uses of CAD to solve real world problems and challenges in Biomedical systems with the help of appropriate case studies and research simulation results. It explains behaviours, concepts, fundamentals, principles, case studies and future research directions including automatic identification of related disorders using CAD.
Present book discusses uses of CAD to solve real world problems and challenges in Biomedical systems with the help of appropriate case studies and research simulation results. It explains behaviours, concepts, fundamentals, principles, case studies and future research directions including automatic identification of related disorders using CAD.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Chapter 1 Electroencephalogram Signals Based Emotion Classification in Parkinson's Disease Using Recurrence Quantification Analysis and Non-Linear Classifiers Chapter 2 Sleep Stage Classification Using DWT and Dispersion Entropy Applied on EEG Signals Chapter 3 Detection of Epileptic Electroencephalogram Signals Employing Visibility Graph Motifs Chapter 4 Effect of Various Standing Poses of Yoga on the Musculoskeletal System Using EMG Chapter 5 Early Detection of Parkinson Disease and SWEDD Using SMOTE and Ensemble Chapter 6 Computer-Aided Design and Diagnosis Method for Cancer Detection Chapter 7 Automated COVID-19 Detection from CT Images Using Deep Learning Chapter 8 Suspicious Region Diagnosis in the Brain: A Guide to Using Brain MRI Sequences Chapter 9 Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network Chapter 10 Positioning the Healthcare Client in Diagnostics and the Validation of Care Intensity Chapter 11 Computer-Aided Diagnosis (CAD) System for Determining Histological Grading of Astrocytoma Based on Ki67 Counting Chapter 12 Improved Classification Techniques for the Diagnosis and Prognosis of Cancer Chapter 13 Discovery of Thyroid Disease Using Different Ensemble Methods with Reduced Error Pruning Technique Chapter 14 Reliable Diagnosis and Prognosis of COVID-19 Chapter 15 Computer-Aided Diagnosis Methods for Non-Invasive Imaging of Sub-Skin Lesions Index
Chapter 1 Electroencephalogram Signals Based Emotion Classification in Parkinson's Disease Using Recurrence Quantification Analysis and Non-Linear Classifiers Chapter 2 Sleep Stage Classification Using DWT and Dispersion Entropy Applied on EEG Signals Chapter 3 Detection of Epileptic Electroencephalogram Signals Employing Visibility Graph Motifs Chapter 4 Effect of Various Standing Poses of Yoga on the Musculoskeletal System Using EMG Chapter 5 Early Detection of Parkinson Disease and SWEDD Using SMOTE and Ensemble Chapter 6 Computer-Aided Design and Diagnosis Method for Cancer Detection Chapter 7 Automated COVID-19 Detection from CT Images Using Deep Learning Chapter 8 Suspicious Region Diagnosis in the Brain: A Guide to Using Brain MRI Sequences Chapter 9 Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network Chapter 10 Positioning the Healthcare Client in Diagnostics and the Validation of Care Intensity Chapter 11 Computer-Aided Diagnosis (CAD) System for Determining Histological Grading of Astrocytoma Based on Ki67 Counting Chapter 12 Improved Classification Techniques for the Diagnosis and Prognosis of Cancer Chapter 13 Discovery of Thyroid Disease Using Different Ensemble Methods with Reduced Error Pruning Technique Chapter 14 Reliable Diagnosis and Prognosis of COVID-19 Chapter 15 Computer-Aided Diagnosis Methods for Non-Invasive Imaging of Sub-Skin Lesions Index
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