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Regression Analysis

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Predictors of High Healthcare Cost Among Patients with Generalized Myasthenia Gravis: A Combined Machine Learning and Regression Approach from a US Payer Perspective.

Applied health economics and health policy
BACKGROUND: High healthcare costs could arise from unmet needs. This study used random forest (RF) and regression methods to identify predictors of high costs from a US payer perspective in patients newly diagnosed with generalized myasthenia gravis ...

Convolutional neural network-based regression analysis to predict subnuclear chromatin organization from two-dimensional optical scattering signals.

Journal of biomedical optics
SIGNIFICANCE: Azimuth-resolved optical scattering signals obtained from cell nuclei are sensitive to changes in their internal refractive index profile. These two-dimensional signals can therefore offer significant insights into chromatin organizatio...

Comparison of Regression Methods to Predict the First Spike Latency in Response to an External Stimulus in Intracellular Recordings for Cerebellar Cells.

Studies in health technology and informatics
The significance of intracellular recording in neurophysiology is emphasized in this article, with considering the functions of neurons, particularly the role of first spike latency in response to external stimuli. The study employs advanced machine ...

Bayesian learning of feature spaces for multitask regression.

Neural networks : the official journal of the International Neural Network Society
This paper introduces a novel approach to learn multi-task regression models with constrained architecture complexity. The proposed model, named RFF-BLR, consists of a randomised feedforward neural network with two fundamental characteristics: a sing...

Mathematical optimization of multilinear and artificial neural network regressions for mineral composition of different tea types infusions.

Scientific reports
The objective of this study was to investigate the change in mineral composition depending on tea variety, tea concentration, and steeping time. Four different tea varieties, black Ceylon (BC), black Turkish (BT), green Ceylon (GC), and green Turkish...

Investigation of a surrogate measure-based safety index for predicting injury crashes at signalized intersections.

Traffic injury prevention
OBJECTIVES: The paper develops a machine learning-based safety index for classifying traffic conflicts that can be used to estimate the frequency of signalized intersection crashes, with a focus on the more severe ones that result in fatal and severe...

Prediction of Fatty Acid Intake from Serum Fatty Acid Levels Using Machine Learning Technique in Women Living in Toyama Prefecture.

Journal of oleo science
Preventing lifestyle-related diseases requires understanding and managing the intake of total fats and specific types of fatty acids, especially trans fatty acids. There are several methods for measuring fat intake, each with its own strengths and li...

A hybrid approach for modeling bicycle crash frequencies: Integrating random forest based SHAP model with random parameter negative binomial regression model.

Accident; analysis and prevention
To effectively capture and explain complex, nonlinear relationships within bicycle crash frequency data and account for unobserved heterogeneity simultaneously, this study proposes a new hybrid framework that combines the Random Forest-based SHapley ...