Medicine Expenditure Prediction via a Variance- Based Generative Adversarial Network

Machine learning (ML) offers a wide range of techniques to predict medicine expenditures using historical expenditures data as well as other healthcare variables. For example, researchers have developed multilayer perceptron (MLP), long short-term memory (LSTM), and convolutional neural network (CNN...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.110947-110958
Hauptverfasser:	Kaushik, Shruti, Choudhury, Abhinav, Natarajan, Sayee, Pickett, Larry A., Dutt, Varun
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Data models Expenditures Gallium nitride Generative adversarial network Generative adversarial networks Health care long short-term memory Machine learning Medical diagnostic imaging Medical services Medicine medicine expenditures multilayer perceptron Multilayer perceptrons Neural networks Prediction models Predictive models regression time-series prediction Variance variance minimization
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