AIMC Topic: Prevalence
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An interpretable machine learning model of cross-sectional U.S. county-level obesity prevalence using explainable artificial intelligence.
PloS one
Oct 5, 2023
BACKGROUND: There is considerable geographic heterogeneity in obesity prevalence across counties in the United States. Machine learning algorithms accurately predict geographic variation in obesity prevalence, but the models are often uninterpretable...
Specialist hybrid models with asymmetric training for malaria prevalence prediction.
Frontiers in public health
Sep 21, 2023
Malaria is a common and serious disease that primarily affects developing countries and its spread is influenced by a variety of environmental and human behavioral factors; therefore, accurate prevalence prediction has been identified as a critical c...
Suitability of machine learning models for prediction of clinically defined Stage III/IV periodontitis from questionnaires and demographic data in Danish cohorts.
Journal of clinical periodontology
Sep 10, 2023
AIM: To evaluate if, and to what extent, machine learning models can capture clinically defined Stage III/IV periodontitis from self-report questionnaires and demographic data.
A statistical comparison between Matthews correlation coefficient (MCC), prevalence threshold, and Fowlkes-Mallows index.
Journal of biomedical informatics
Jun 21, 2023
Even if assessing binary classifications is a common task in scientific research, no consensus on a single statistic summarizing the confusion matrix has been reached so far. In recent studies, we demonstrated the advantages of the Matthews correlati...
Identifying the Influencing Factors of Depressive Symptoms among Nurses in China by Machine Learning: A Multicentre Cross-Sectional Study.
Journal of nursing management
May 15, 2023
BACKGROUND: Nurses' high workload can result in depressive symptoms. However, the research has underexplored the internal and external variables, such as organisational support, career identity, and burnout, which may predict depressive symptoms amon...
Interstitial Lung Abnormalities at CT in the Korean National Lung Cancer Screening Program: Prevalence and Deep Learning-based Texture Analysis.
Radiology
Apr 25, 2023
Background Interstitial lung abnormalities (ILAs) are associated with worse clinical outcomes, but ILA with lung cancer screening CT has not been quantitatively assessed. Purpose To determine the prevalence of ILA at CT examinations from the Korean N...
Quantitative Texture Analysis of Interstitial Lung Abnormalities Opens a New Chapter for Chest CT Interpretation.
Radiology
Apr 25, 2023
Prevalence of depressive symptoms and associated factors during the COVID-19 pandemic: A national-based study.
Journal of affective disorders
Apr 17, 2023
BACKGROUND: Previous studies have reported that the prevalence of depression and depressive symptoms was significantly higher than that before the COVID-19 pandemic. This study aimed to explore the prevalence of depressive symptoms and evaluate the i...
Multicentre external validation of a commercial artificial intelligence software to analyse chest radiographs in health screening environments with low disease prevalence.
European radiology
Jan 10, 2023
OBJECTIVES: To externally validate the performance of a commercial AI software program for interpreting CXRs in a large, consecutive, real-world cohort from primary healthcare centres.
Uretero-enteric Strictures After Robot Assisted Radical Cystectomy: Prevalence and Management Over Two Decades.
Clinical genitourinary cancer
Oct 12, 2022
INTRODUCTION: To evaluate the prevalence, predictors, management, and trends for ureteroenteric strictures (UES) after robot-assisted radical cystectomy (RARC).
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