AI Medical Compendium Journal:
BMC public health

Showing 1 to 10 of 78 articles

Comparison of spatial prediction models from Machine Learning of cholangiocarcinoma incidence in Thailand.

BMC public health
BACKGROUND: Cholangiocarcinoma (CCA) poses a significant public health challenge in Thailand, with notably high incidence rates. This study aimed to compare the performance of spatial prediction models using Machine Learning techniques to analyze the...

Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability.

BMC public health
BACKGROUND: Mild Cognitive Impairment (MCI) is a critical transitional stage between normal aging and Alzheimer's disease, and its early identification is essential for delaying disease progression.

Application of machine learning algorithms to model predictors of informed contraceptive choice among reproductive age women in six high fertility rate sub Sahara Africa countries.

BMC public health
INTRODUCTION: Informed contraceptive choice is declared when a woman selects a methods of contraceptive after receiving comprehensive information on available alternatives, side effects, and management if adverse effect happens. Access to contracepti...

Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal study.

BMC public health
BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) continues to rise among middle-aged and elderly populations, affecting not only physical health but also significantly increasing the risk of depression. This study aims to construc...

Evaluation of artificial intelligence (AI) chatbots for providing sexual health information: a consensus study using real-world clinical queries.

BMC public health
INTRODUCTION: Artificial Intelligence (AI) chatbots could potentially provide information on sensitive topics, including sexual health, to the public. However, their performance compared to nurses and across different AI chatbots, particularly in the...

Prediction models based on machine learning algorithms for COVID-19 severity risk.

BMC public health
BACKGROUND: The World Health Organization has highlighted the risk of Disease X, urging pandemic preparedness. Coronavirus disease 2019 (COVID-19) could be the first Disease X; therefore, understanding the epidemiological experiences of COVID-19 is c...

Exploring the potential and limitations of deep learning and explainable AI for longitudinal life course analysis.

BMC public health
BACKGROUND: Understanding the complex interplay between life course exposures, such as adverse childhood experiences and environmental factors, and disease risk is essential for developing effective public health interventions. Traditional epidemiolo...

Random forest algorithm for predicting tobacco use and identifying determinants among pregnant women in 26 sub-Saharan African countries: a 2024 analysis.

BMC public health
INTRODUCTION: Tobacco use during pregnancy is a significant public health concern, associated with adverse maternal and neonatal outcomes. Despite its critical importance, comprehensive data on tobacco use among pregnant women in sub-Saharan Africa i...

Domestic violence and childhood trauma among married women using machine learning approach: a cross-sectional study.

BMC public health
BACKGROUND: Globally, 27% of ever-partnered women aged 15-49 have experienced physical, sexual, or intimate partner violence at least once in their lifetime. In Saudi Arabia, domestic violence (DV) remains a concern despite cultural and economic adva...