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Approximate methods: application of numerical techniques.
Davatzikos, C. et al. Classifying spatial patterns of brain activity with machine learning methods: application to lie detection.
Sahai, H. & Ojeda, M. M. Analysis of Variance for Random Models: Vol. 1 Balanced Data, Theory, Methods, Application, and Data Analysis.
This chapter investigates complex variable methods' application to problems of engineering interest.
Linearized reference tissue parametric imaging methods: application to [11C]DASB positron emission tomography studies of the serotonin transporter in human brain.
So far, significant progress has been made in the development of synthetic methods, application to engineering polymers, and the investigation of major engineering properties.
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Balk, D. et al. Determining global population distribution: methods, applications and data.
Song, Y. Y. & Lu, Y. Decision tree methods: applications for classification and prediction.
Tran, C. & Damaser, M. Stem cells as drug delivery methods: applications of stem cell secretome for regeneration.
Fig. 1 Data-driven methods applications.
Papers describe research on problems and methods, applications research, and issues of research methodology.
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