Machine Learning, Big Data, and Iot for Medical Informatics

ISBN-13: 9780128217771 / Angielski / Miękka / 2021 / 458 str.

Pardeep Kumar; Yugal Kumar; Mohamed A. Tawhid

Spis treści

1. Predictive analytics and machine learning for medical informatics: A survey of tasks and techniques 2. Geolocation-aware IoT and cloud-fog-based solutions for healthcare 3. Machine learning vulnerability in medical imaging 4. Skull stripping and tumor detection using 3D U-Net 5. Cross color dominant deep autoencoder for quality enhancement of laparoscopic video: A hybrid deep learning and range-domain filtering-based approach 6. Estimating the respiratory rate from ECG and PPG using machine learning techniques 7. Machine learning-enabled Internet of Things for medical informatics 8. Edge detection-based segmentation for detecting skin lesions 9. A review of deep learning approaches in glove-based gesture classification 10. An ensemble approach for evaluating the cognitive performance of human population at high altitude 11. Machine learning in expert systems for disease diagnostics in human healthcare 12. An entropy-based hybrid feature selection approach for medical datasets 13. Machine learning for optimizing healthcare resources 14. Interpretable semi-supervised classifier for predicting cancer stages 15. Applications of blockchain technology in smart healthcare: An overview 16. Prediction of leukemia by classification and clustering techniques 17. Performance evaluation of fractal features toward seizure detection from electroencephalogram signals 18. Integer period discrete Fourier transform-based algorithm for the identification of tandem repeats in the DNA sequences 19. A blockchain solution for the privacy of patients' medical data 20. A novel approach for securing e-health application in a cloud environment 21. An ensemble classifier approach for thyroid disease diagnosis using the AdaBoostM algorithm 22. A review of deep learning models for medical diagnosis 23. Machine learning in precision medicine