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Detection of C-shaped mandibular second molars on panoramic radiographs using deep convolutional neural networks.

Clinical oral investigations
OBJECTIVES: The C-shaped mandibular second molars (MSMs) may pose an endodontic challenge. The aim of this study was to develop a convolutional neural network (CNN)-based deep learning system for the diagnosis of C-shaped MSMs on panoramic radiograph...

An interpretable machine learning scoring tool for estimating time to recurrence readmissions in stroke patients.

International journal of medical informatics
BACKGROUND: Stroke recurrence readmission poses an additional burden on both patients and healthcare systems. Risk stratification aims to accurately divide patients into groups to provide targeted interventions at reducing readmission. To accurately ...

Accurate and efficient prediction of atmospheric PM, PM, PM, and O concentrations using a customized software package based on a machine-learning algorithm.

Chemosphere
Particulate matter (PM) and ozone (O) pollution have been attracting increasing attention recently due to their severe harm to human health. PM and O are secondary pollutants, and there remain significant challenges in accurately and efficiently pred...

Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study.

Cardiovascular diabetology
BACKGROUND: Heart failure combined with hypertension is a major contributor for elderly patients (≥ 65 years) to in-hospital mortality. However, there are very few models to predict in-hospital mortality in such elderly patients. We aimed to develop ...

Development of a machine learning-based risk assessment model for loneliness among elderly Chinese: a cross-sectional study based on Chinese longitudinal healthy longevity survey.

BMC geriatrics
BACKGROUND: Loneliness is prevalent among the elderly and has intensified due to global aging trends. It adversely affects both mental and physical health. Traditional scales for measuring loneliness may yield biased results due to varying definition...

Comparative analysis of volatility forecasting for healthcare stock indices amid public health crises: a study based on the Bayes-CNN model.

Frontiers in public health
In recent years, public health events have significantly impacted various aspects of human production and daily life, particularly in the domains of disease transmission and economic stability. While many scholars have primarily focused on the influe...

Water environment risk prediction method based on convolutional neural network-random forest.

Marine pollution bulletin
The accelerated processes of urbanization and industrialization globally have resulted in an increased risk to aquatic environments, posing a significant threat to the sustainable management of water resources and the health of ecosystems. Accurate p...

A New Research Model for Artificial Intelligence-Based Well-Being Chatbot Engagement: Survey Study.

JMIR human factors
BACKGROUND: Artificial intelligence (AI)-based chatbots have emerged as potential tools to assist individuals in reducing anxiety and supporting well-being.

Improving methylmalonic acidemia (MMA) screening and MMA genotype prediction using random forest classifier in two Chinese populations.

European journal of medical research
BACKGROUND: Methylmalonic acidemia (MMA) is one of the most common hereditary organic acid metabolism disorders that endangers the lives and health of infants and children. Early detection and intervention before the appearance of a newborn's clinica...

Improving the construction and prediction strategy of the Air Quality Health Index (AQHI) using machine learning: A case study in Guangzhou, China.

Ecotoxicology and environmental safety
Effectively capturing the risk of air pollution and informing residents is vital to public health. The widely used Air Quality Index (AQI) has been criticized for failing to accurately represent the non-threshold linear relationship between air pollu...