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Linear Models

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AGL-Net: An Efficient Neural Network for EEG-Based Driver Fatigue Detection.

Journal of integrative neuroscience
BACKGROUND: In recent years, road traffic safety has become a prominent issue due to the worldwide proliferation of vehicles on roads. The challenge of driver fatigue detection involves balancing the efficiency and accuracy of the detection process. ...

The use of simple structural parameters of organic compounds to assess their PUF-air partition coefficients.

Chemosphere
A novel approach is introduced for the reliable prediction of PUF-air partition coefficients of organic compounds, which can determine the environmental fate of organic compounds during interactions with air, soil, and water. The biggest accessible m...

Automated size-specific dose estimates framework in thoracic CT using convolutional neural network based on U-Net model.

Journal of applied clinical medical physics
PURPOSE: This study aimed to develop an automated method that uses a convolutional neural network (CNN) for calculating size-specific dose estimates (SSDEs) based on the corrected effective diameter (D ) in thoracic computed tomography (CT).

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study.

Journal of medical Internet research
BACKGROUND: Sentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its colloqu...

Machine learning can predict anterior elevation after reverse total shoulder arthroplasty: A new tool for daily outpatient clinic?

Musculoskeletal surgery
The aim of the present study was to individuate and compare specific machine learning algorithms that could predict postoperative anterior elevation score after reverse shoulder arthroplasty surgery at different time points. Data from 105 patients wh...

Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: A Deep Learning Approach to Monitor Obesity and Body Shape in Individuals in Their 20s and 30s.

Sensors (Basel, Switzerland)
This study demonstrates how to generate a three-dimensional (3D) body model through a small number of images and derive body values similar to the actual values using generated 3D body data. In this study, a 3D body model that can be used for body ty...

Predicting saturated and near-saturated hydraulic conductivity using artificial neural networks and multiple linear regression in calcareous soils.

PloS one
Hydraulic conductivity (Kψ) is one of the most important soil properties that influences water and chemical movement within the soil and is a vital factor in various management practices, like drainage, irrigation, erosion control, and flood protecti...

ML interpretability: Simple isn't easy.

Studies in history and philosophy of science
The interpretability of ML models is important, but it is not clear what it amounts to. So far, most philosophers have discussed the lack of interpretability of black-box models such as neural networks, and methods such as explainable AI that aim to ...

Using machine learning and partial dependence to evaluate robustness of best linear unbiased prediction (BLUP) for phenotypic values.

Journal of applied genetics
Best linear unbiased prediction (BLUP) is widely used in plant research to address experimental variation. For phenotypic values, BLUP accuracy is largely dependent on properly controlled experimental repetition and how variable components are outlin...

Risk adjustment for regional healthcare funding allocations with ensemble methods: an empirical study and interpretation.

The European journal of health economics : HEPAC : health economics in prevention and care
We experiment with recent ensemble machine learning methods in estimating healthcare costs, utilizing Finnish data containing rich individual-level information on healthcare costs, socioeconomic status and diagnostic data from multiple registries. Ou...