AIMC Topic: Machine Learning

Clear Filters Showing 11191 to 11200 of 34417 articles

Cognitive workload classification of law enforcement officers using physiological responses.

Applied ergonomics
Motor vehicle crashes (MVCs) are a leading cause of death for law enforcement officers (LEOs) in the U.S. LEOs and more specifically novice LEOs (nLEOs) are susceptible to high cognitive workload while driving which can lead to fatal MVCs. The object...

Development and application of machine learning models for prediction of soil available cadmium based on soil properties and climate features.

Environmental pollution (Barking, Essex : 1987)
Identifying the key influencing factors in soil available cadmium (Cd) is crucial for preventing the Cd accumulation in the food chain. However, current experimental methods and traditional prediction models for assessing available Cd are time-consum...

Machine learning to predict the relationship between Vibrio spp. concentrations in seawater and oysters and prevalent environmental conditions.

Food research international (Ottawa, Ont.)
Vibrio parahaemolyticus and Vibrio vulnificus are bacteria with a significant public health impact. Identifying factors impacting their presence and concentrations in food sources could enable the identification of significant risk factors and preven...

Accuracy of machine learning in preoperative identification of genetic mutation status in lung cancer: A systematic review and meta-analysis.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: We performed this systematic review and meta-analysis to investigate the performance of ML in detecting genetic mutation status in NSCLC patients.

Graph machine learning for integrated multi-omics analysis.

British journal of cancer
Multi-omics experiments at bulk or single-cell resolution facilitate the discovery of hypothesis-generating biomarkers for predicting response to therapy, as well as aid in uncovering mechanistic insights into cellular and microenvironmental processe...

A prospective cohort-based artificial intelligence evaluation system for the protective efficacy and immune response of SARS-CoV-2 inactivated vaccines.

International immunopharmacology
BACKGROUND: Novel coronaviruses constitute a significant health threat, prompting the adoption of vaccination as the primary preventive measure. However, current evaluations of immune response and vaccine efficacy are deemed inadequate.

Precision healthcare: A deep dive into machine learning algorithms and feature selection strategies for accurate heart disease prediction.

Computers in biology and medicine
This paper presents a comprehensive exploration of machine learning algorithms (MLAs) and feature selection techniques for accurate heart disease prediction (HDP) in modern healthcare. By focusing on diverse datasets encompassing various challenges, ...

Examining nonlinear effects of socioecological drivers on urban solar energy development in China using machine learning and high-dimensional data.

Journal of environmental management
In the context of carbon neutrality target, renewable energy sources have been transforming from "supplementary energy" to "main energy", which have promoted the green and low-carbon transition of global energy supply system. In-depth analyzing the s...

Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules.

Expert opinion on drug discovery
INTRODUCTION: Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structur...