AIMC Topic: Regression Analysis
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Alternative assessment of machine learning to polynomial regression in response surface methodology for predicting decolorization efficiency in textile wastewater treatment.
Chemosphere
Dec 20, 2024
This study investigated the potential of machine learning (ML) as a substitute for polynomial regression in conventional response surface methodology (RSM) for decolorizing textile wastewater via a UV/HO process. While polynomial regression offers li...
Tensor Coupled Learning of Incomplete Longitudinal Features and Labels for Clinical Score Regression.
IEEE transactions on pattern analysis and machine intelligence
Dec 4, 2024
Longitudinal data with incomplete entries pose a significant challenge for clinical score regression over multiple time points. Although many methods primarily estimate longitudinal scores with complete baseline features (i.e., features collected at ...
Prediction of the risk of mortality in older patients with coronavirus disease 2019 using blood markers and machine learning.
Frontiers in immunology
Nov 1, 2024
INTRODUCTION: The mortality rate among older people infected with severe acute respiratory syndrome coronavirus 2 is alarmingly high. This study aimed to explore the predictive value of a novel model for assessing the risk of death in this vulnerable...
Machine learning assisted rapid approach for quantitative prediction of biochemical parameters of blood serum with FTIR spectroscopy.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Oct 12, 2024
This study develops regression models for predicting blood biochemical data using Fourier-transform infrared spectroscopy (FTIR) analysis. Absorption at specific wavelengths of blood serum is revealed to have strong correlations with biochemical para...
Weighted Expectile Regression Neural Networks for Right Censored Data.
Statistics in medicine
Sep 29, 2024
As a favorable alternative to the censored quantile regression, censored expectile regression has been popular in survival analysis due to its flexibility in modeling the heterogeneous effect of covariates. The existing weighted expectile regression ...
Investigation of a surrogate measure-based safety index for predicting injury crashes at signalized intersections.
Traffic injury prevention
Sep 26, 2024
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...
Progression to refractory status epilepticus: A machine learning analysis by means of classification and regression tree analysis.
Epilepsy & behavior : E&B
Sep 21, 2024
BACKGROUND AND OBJECTIVES: to identify predictors of progression to refractory status epilepticus (RSE) using a machine learning technique.
Prediction of Fatty Acid Intake from Serum Fatty Acid Levels Using Machine Learning Technique in Women Living in Toyama Prefecture.
Journal of oleo science
Sep 20, 2024
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
Sep 16, 2024
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 ...
Prediction model for lateral lymph node metastasis of papillary thyroid carcinoma in children and adolescents based on ultrasound imaging and clinical features: a retrospective study.
BMC medical imaging
Aug 29, 2024
BACKGROUND: The presence of lateral lymph node metastases (LNM) in paediatric patients with papillary thyroid cancer (PTC) is an independent risk factor for recurrence. We aimed to identify risk factors and establish a prediction model for lateral LN...
Thyroid Cancer, Papillary
Predictive Learning Models
Regression Analysis
Predictive Value of Tests
Humans
Area Under Curve
Retrospective Studies
Reference Values
Risk Assessment
Female
ROC Curve
Adolescent
Risk Factors
Lymph Nodes
Thyroid Neoplasms
Young Adult
Lymphatic Metastasis
Ultrasonography
Male
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