AIMC Topic: Linear Models
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Modelling for disability: How does artificial intelligence affect unemployment among people with disability? An empirical analysis of linear and nonlinear effects.
Research in developmental disabilities
Apr 24, 2024
There is a growing debate among scholars regarding the impact of artificial intelligence (AI) on the employment opportunities and professional development of people with disability. Although there has been an increasing body of empirical research on ...
Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks.
Sensors (Basel, Switzerland)
Apr 14, 2024
The accurate estimation of energy expenditure from simple objective accelerometry measurements provides a valuable method for investigating the effect of physical activity (PA) interventions or population surveillance. Methods have been evaluated pre...
Improving the operational forecasts of outdoor Universal Thermal Climate Index with post-processing.
International journal of biometeorology
Mar 5, 2024
The Universal Thermal Climate Index (UTCI) is a thermal comfort index that describes how the human body experiences ambient conditions. It has units of temperature and considers physiological aspects of the human body. It takes into account the effec...
Prescription eyeglasses as a forensic physical evidence: Prediction of age based on refractive error measures using machine learning algorithm.
Journal of forensic sciences
Feb 23, 2024
Refractive errors (RE) are commonly reported visual impairment problems worldwide. Previous clinical studies demonstrated age-related changes in human eyes. We hypothesized that the binocular RE metrics including sphere and cylinder power, axis orien...
Quantitative structure-property relationship modelling on autoignition temperature: evaluation and comparative analysis.
SAR and QSAR in environmental research
Feb 19, 2024
The autoignition temperature (AIT) serves as a crucial indicator for assessing the potential hazards associated with a chemical substance. In order to gain deeper insights into model performance and facilitate the establishment of effective methodolo...
Automated size-specific dose estimates framework in thoracic CT using convolutional neural network based on U-Net model.
Journal of applied clinical medical physics
Jan 31, 2024
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
Jan 30, 2024
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
Jan 24, 2024
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...
Predicting saturated and near-saturated hydraulic conductivity using artificial neural networks and multiple linear regression in calcareous soils.
PloS one
Jan 10, 2024
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...
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
Jan 3, 2024
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...
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