AIMC Topic: Machine Learning

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Integrating CT radiomics and clinical features using machine learning to predict post-COVID pulmonary fibrosis.

Respiratory research Jul 2, 2025
BACKGROUND: The lack of reliable biomarkers for the early detection and risk stratification of post-COVID-19 pulmonary fibrosis (PCPF) underscores the urgency advanced predictive tools. This study aimed to develop a machine learning-based predictive ...
Radiomics Lung Humans Retrospective Studies Male Cohort Studies Tomography, X-Ray Computed Machine Learning Middle Aged Predictive Value of Tests Female COVID-19 Pulmonary Fibrosis Aged
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Exploring the complex associations between community public spaces and healthy aging: an explainable analysis using catboost and SHAP.

BMC public health Jul 2, 2025
BACKGROUND: As global aging accelerates, community public spaces (CPS) are increasingly recognized as vital for promoting healthy aging. However, existing research often employs linear analytical methods or focuses on single health dimensions, overlo...
Aged Aged, 80 and over Male Middle Aged Healthy Aging Humans Machine Learning Female China Residence Characteristics Boosting Machine Learning Algorithms
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Machine learning-based integration identifies plasma cells-related gene signature ST6GAL1 in idiopathic pulmonary fibrosis.

BMC pulmonary medicine Jul 2, 2025
BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a rare, progressive, and fibrotic disease with poor prognosis that lacks treatment options. As a major component of the lung adaptive immune system, plasma cells play a crucial regulatory role during...
Idiopathic Pulmonary Fibrosis Plasma Cells Sialyltransferases Male Gene Expression Profiling Transcriptome Mice Female Aged Animals Humans Machine Learning Prognosis
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Spatial analysis of county-level determinants of overdose mortality in the United States using spatial machine learning.

BMC public health Jul 2, 2025
In recent years, there has been a growing body of literature on identifying effective determinants for modeling the spatial variation of overdose rates, addressing this emerging public health concern globally. We compiled a range of widely recognized...
Humans Machine Learning United States Spatial Analysis Drug Overdose
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Enhanced machine learning models for predicting three-year mortality in Non-STEMI patients aged 75 and above.

BMC geriatrics Jul 2, 2025
BACKGROUND: Non-ST segment elevation myocardial infarction (Non-STEMI) is a severe cardiovascular condition mainly affecting individuals aged 75 and above, who are at higher risk of mortality due to age-related vulnerabilities and other health issues...
Male Cohort Studies Predictive Value of Tests Myocardial Infarction Mortality Prognosis Humans Female Machine Learning Aged Aged, 80 and over
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Development of an electronic health record-based Human Immunodeficiency Virus (HIV) risk prediction model for women, incorporating social determinants of health.

BMC public health Jul 2, 2025
BACKGROUND: Human Immunodeficiency Virus (HIV) pre-exposure prophylaxis (PrEP) prevents HIV transmission but has low uptake among women. Identifying women who could benefit from PrEP remains a challenge. This study developed a women-specific model to...
Pre-Exposure Prophylaxis Southeastern United States Risk Assessment Case-Control Studies Humans Female Machine Learning Adult HIV Infections Electronic Health Records Middle Aged Social Determinants of Health
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Methodological conduct and risk of bias in studies on prenatal birthweight prediction models using machine learning techniques: a systematic review.

BMC pregnancy and childbirth Jul 2, 2025
OBJECTIVE: To assess the methodological quality and the risk of bias, of studies that developed prediction models using Machine Learning (ML) techniques to estimate prenatal birthweight.
Birth Weight Fetal Weight Infant, Newborn Reproducibility of Results Bias Humans Machine Learning Research Design Pregnancy Female
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Prediction of caesarean section birth using machine learning algorithms among pregnant women in a district hospital in Ghana.

BMC pregnancy and childbirth Jul 2, 2025
BACKGROUND: Machine learning algorithms may contribute to improving maternal and child health, including determining the suitability of caesarean section (CS) births in low-resource countries. Despite machine learning algorithms offering a more robus...
Humans Machine Learning Cesarean Section Young Adult Adult Cross-Sectional Studies Algorithms Retrospective Studies Pregnancy Female Support Vector Machine ROC Curve Bayes Theorem Decision Support Systems, Clinical Ghana Logistic Models Hospitals, District
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Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China.

BMC geriatrics Jul 2, 2025
OBJECTIVE: Depression in older adults is a growing public health concern, yet there is still a lack of convenient and real-time methods for depressive symptoms identification. This study aims to develop a gait-based depression recognition method for ...
Gait Middle Aged China Depression Humans Machine Learning Aged Female Aged, 80 and over Cross-Sectional Studies Male
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Identification of MEG3 and MAPK3 as potential therapeutic targets for osteoarthritis through multiomics integration and machine learning.

Scientific reports Jul 2, 2025
Knee osteoarthritis (KOA) is a prevalent degenerative joint disorder, yet its underlying molecular mechanisms remain puzzling. This study aimed to uncover the genes with a causal relationship to KOA using Mendelian randomization (MR), transcriptomic ...
Humans Machine Learning Gene Expression Profiling Mendelian Randomization Analysis Osteoarthritis, Knee Quantitative Trait Loci Mitogen-Activated Protein Kinase 3 Genome-Wide Association Study ROC Curve Multiomics RNA, Long Noncoding
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