This book presents the integration of machine learning and deep learning algorithms that can be applied in the healthcare sector to reduce the time needed by doctors, radiologists, and other medical professionals to analyze, predict, and diagnose conditions with accurate results.
This book presents the integration of machine learning and deep learning algorithms that can be applied in the healthcare sector to reduce the time needed by doctors, radiologists, and other medical professionals to analyze, predict, and diagnose conditions with accurate results.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamilnadu, India. Dr Kishore Balasubramanian is an Assistant Professor (Senior Scale) in the Department of EEE at Dr. Mahalingam College of Engineering & Technology, India. Dr. Le Anh Ngoc is a Vice Dean of Electronics and Telecommunications Faculty, Electric Power University, Hanoi, Vietnam.
Inhaltsangabe
Chapter 1. A Comprehensive Study on MLP and CNN, and the Implementation of Multi-Class Image Classification using Deep CNN Chapter 2. An Efficient Technique for Image Compression and Quality Retrieval in Diagnosis of Brain Tumour Hyper Spectral Image Chapter 3. Classification of Breast Thermograms using a Multi-layer Perceptron with Back Propagation Learning Chapter 4. Neural Networks for Medical Image Computing Chapter 5. Recent Trends in Bio-Medical Waste, Challenges and Opportunities Chapter 6. Teager-Kaiser Boost Clustered Segmentation of Retinal Fundus Images for Glaucoma Detection Chapter 7. IoT-Based Deep Neural Network Approach for Heart Rate and SpO2 Prediction Chapter 8. An Intelligent System for Diagnosis and Prediction of Breast Cancer Malignant Features using Machine Learning Algorithms Chapter 9. Medical Image Classification with Artificial and Deep Convolutional Neural Networks: A Comparative Study Chapter 10. Convolutional Neural Network for Classification of Skin Cancer Images Chapter 11. Application of Artificial Intelligence in Medical Imaging Chapter 12. Machine Learning Algorithms Used in Medical Field with a Case Study Chapter 13. Dual Customized U-Net-based Based Automated Diagnosis of Glaucoma Chapter 14. MuSCF-Net: Multi-scale, Multi-Channel Feature Network using Resnet-Based Attention Mechanism for Breast Histopathological Image Classification Chapter 15. Artificial Intelligence is Revolutionizing Cancer Research Chapter 16. Deep Learning to Diagnose Diseases and Security in 5G Healthcare InformaticsChapter 17. New Approaches in Machine-based Image Analysis for Medical Oncology Chapter 18. Performance Analysis of Deep Convolutional Neural Networks for Diagnosing COVID-19: Data to Deployment Chapter 19. Stacked Auto Encoder Deep Neural Network with Principal Components Analysis for Identification of Chronic Kidney Disease
Chapter 1. A Comprehensive Study on MLP and CNN, and the Implementation of Multi-Class Image Classification using Deep CNN Chapter 2. An Efficient Technique for Image Compression and Quality Retrieval in Diagnosis of Brain Tumour Hyper Spectral Image Chapter 3. Classification of Breast Thermograms using a Multi-layer Perceptron with Back Propagation Learning Chapter 4. Neural Networks for Medical Image Computing Chapter 5. Recent Trends in Bio-Medical Waste, Challenges and Opportunities Chapter 6. Teager-Kaiser Boost Clustered Segmentation of Retinal Fundus Images for Glaucoma Detection Chapter 7. IoT-Based Deep Neural Network Approach for Heart Rate and SpO2 Prediction Chapter 8. An Intelligent System for Diagnosis and Prediction of Breast Cancer Malignant Features using Machine Learning Algorithms Chapter 9. Medical Image Classification with Artificial and Deep Convolutional Neural Networks: A Comparative Study Chapter 10. Convolutional Neural Network for Classification of Skin Cancer Images Chapter 11. Application of Artificial Intelligence in Medical Imaging Chapter 12. Machine Learning Algorithms Used in Medical Field with a Case Study Chapter 13. Dual Customized U-Net-based Based Automated Diagnosis of Glaucoma Chapter 14. MuSCF-Net: Multi-scale, Multi-Channel Feature Network using Resnet-Based Attention Mechanism for Breast Histopathological Image Classification Chapter 15. Artificial Intelligence is Revolutionizing Cancer Research Chapter 16. Deep Learning to Diagnose Diseases and Security in 5G Healthcare InformaticsChapter 17. New Approaches in Machine-based Image Analysis for Medical Oncology Chapter 18. Performance Analysis of Deep Convolutional Neural Networks for Diagnosing COVID-19: Data to Deployment Chapter 19. Stacked Auto Encoder Deep Neural Network with Principal Components Analysis for Identification of Chronic Kidney Disease
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