… in books on data mining and machine learning, is a classification problem. It comes from a …
world have done trials on the use of aspirin to ward off heart attacks. The different trials are in …

… variety of artificial intelligence classification methods of sleep … and classification based on
deep learning, and the analysis … methods, and point out that the multi task analyses with deep …

… The result is compared to the result of other state-of-art methods. … Prediction of short-term
re-admission risk of diabetes mellitus through data balance processing data set 图7. 通过数据…

… this problem, we propose an automatic sleep scoring method … use of a deep convolutional
neural network (CNN) on raw EEG samples for supervised learning of sleep stage prediction, …

… Aiming at the problem that it is difficult to determine the modeling factors and the non-linear
runoff prediction modeling in runoff prediction modeling, this paper uses a homogeneous …

… Selecting and using learning strategies: Teachers should model for students how they make
… about the strategies they would implement to accomplish the intended learning outcomes. …

… Heart diseases are one of the primary causes of death worldwide. A key factor to accurately
… on applying deep learning methods to medical image segmentation, particularly cardiac MRI …

… the predictive performance may be further improved. [Conclusions] Comparative experiments
show that the proposed method … an efficient method for coronary heart disease prediction. It …

… in the machine learning. In this paper, we propose a prediction framework on heart failure
… as to provide effective information for auxiliary cure and diagnosis of the heart failure. The …

… early prediction and prevention of heart disease. In order to address … problems of low accuracy
of heart disease prediction models based on machine learning, a heart disease prediction …