Titlebook: Enhanced Telemedicine and e-Health; Advanced IoT Enabled Gonçalo Marques,Akash Kumar Bhoi,Begonya Garcia-Za Book 2021 The Editor(s) (if app

调味品

无表情

用肘

Fluctuate

Disease Prediction Using Artificial Intelligence: A Case Study on Epileptic Seizure Predictiontion and detection approach based on deep learning is also presented. Since Deep Learning can automatically extract and learn features, the electroencephalography (EEG) time series are fed into the deep learning model. Deep Learning has been utilized in the prediction and detection of epileptic seiz

高射炮

A Novel Wrapper-Based Feature Selection for Heart Failure Prediction Using an Adaptive Particle Swarport Vector Machine (SVM), Decision Tree (DT), K–Nearest Neighbor, Naïve Bayesian Classifier (NBC), Random Forest (RF), and Logistic Regression (LR). The results of our method show not only that much fewer features are needed, but also higher accuracy can be accomplished, 81% for Adaptive Particle S

Parameter

neuron

insincerity

bonnet