Reliable quality and outcomes assessment depends on the ability to distinguish between T1MI and T2MI in administrative claims data. As such, we aimed to develop a classification algorithm to ...

Noise-signal ratio (NSR). Classification, as one of the most important techniques in data mining, has a wide applicable range, and many classification algorithms have been proposed so far. According ...

a single-trial P300 classification algorithm based on multiplayer data fusion convolutional neural network (CNN) is proposed to construct a centralized collaborative brain-computer interfaces (cBCI) ...

Clinical Information and Decision Making (1677) Big Data (283) Methods and Instruments in Medical Informatics (166) Development and Evaluation of Research Methods, Instruments and Tools (644) Tools, ...

meaning it is the algorithms that turn a data set into a model. Which kind of algorithm works best (supervised, unsupervised, classification, regression, etc.) depends on the kind of problem you ...

but the classic data classification algorithms mainly use numeric as the basis of classification modeling or put the high accuracy as the only index of classification model, and these classification ...

Generally, the accuracy of fault classification algorithms is evaluated by simulation data, which shows quite different characteristics from real fault data. Also, most of the previous works on fault ...

A team of researchers has shown that even small-scale quantum computers can enhance machine learning performance, using a ...