AIMC Topic: Linear Models

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ReaGP: integrating residual units and attention mechanisms in convolution neural network for genomic prediction.

Genetics, selection, evolution : GSE
BACKGROUND: Various methods have been widely utilized to estimate the genomic breeding values (GEBVs) for genomic prediction. Traditional approaches often relied on the assumption of linear regression models, which struggle to effectively capture the...

Prediction of urban heat island intensity based on multiple linear regression and deep learning.

PloS one
The rapid urbanization process has led to many prominent environmental issues in urban areas, resulting from a drastic change in land use. The Urban Heat Island (UHI) effect is of particular concern because it has a significant impact on the livabili...

Health-related quality of life among healthcare workers: a comparative analysis using regression, conditional tree and forests.

BMC public health
BACKGROUND: Considering the potential importance of health care workers (HCWs) in maintaining and improving the health of society, we decided to investigate the factors affecting the health-related quality of life (HRQoL) of HCWs using machine learni...

Wave masking enhances electrocardiogram reconstruction with linear regression.

Scientific reports
Electrocardiogram (ECG) reconstruction involves synthesizing leads from a reduced or alternative lead set. While ECG leads are generally considered linearly related, recording distortions and individual differences make perfect replication difficult,...

Application of generalized linear mixed effects random forest for identifying risk factors of prediabetes in Tehran Lipid and Glucose Study.

Scientific reports
Prediabetes is a major risk factor for the development of diabetes, defined by blood glucose levels that are elevated but not yet high enough to meet the diagnostic criteria for Diabetes Mellitus. This condition is often clinically "silent" yet it ca...

CattleNet-XAI: An explainable CNN framework for efficient cattle weight estimation.

PloS one
Accurate estimation of cattle weight is essential for effective farm management, health assessment, and productivity optimization. Traditional manual methods for weight estimation, however, are labor-intensive, time-consuming, and prone to inaccuraci...

T10SLRE: A novel ensemble learning approach for rapid and non-destructive prediction of bread loaf volume in wheat using NIR spectroscopy.

Food chemistry
Bread loaf volume is a critical indicator of wheat processing quality, but conventional bread-making tests are laborious and time-consuming. This study evaluated near-infrared spectroscopy combined with machine learning for rapid prediction of loaf v...

Prediction-powered inference for clinical trials: application to linear covariate adjustment.

BMC medical research methodology
Prediction-powered inference (PPI) (Angelopoulos et al., Science 382(6671):669-674, 2023) and its subsequent development called PPI++ (Angelopoulos et al., 2023) provide a novel approach to standard statistical estimation, leveraging machine learning...

A hybrid approach for forecasting peak expiratory flow rate in asthma patients using combined linear regression and random forest model.

PloS one
Asthma is a frequent and long-lasting disorder associated with airway inflammation. The disease severity may lead to serious health concerns and even mortality. In this work, we propose a novel hybrid approach using machine learning models and simila...

Machine learning-based academic performance prediction with explainability for enhanced decision-making in educational institutions.

Scientific reports
Education is crucial for the growth of effective life skills and the allocation of needed resources. Higher education institutions are adopting advanced technologies, such as artificial intelligence (AI), to enhance traditional teaching methods. Pred...