AIMC Topic: Prevalence

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Identification of Nocturnal Leg Cramps and Affecting Factors in COPD Patients: Logistic Regression and Artificial Neural Network.

Clinical nursing research Sep 20, 2024
Although there are many sleep-related complaints in chronic obstructive pulmonary disease (COPD) patients, nocturnal leg cramps have not been adequately and extensively studied. This study fills a significant gap in the literature by determining the ...
Risk Factors Aged Pulmonary Disease, Chronic Obstructive Male Middle Aged Humans Neural Networks, Computer Female Prevalence Case-Control Studies Logistic Models Sleep-Wake Transition Disorders
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Computer Vision Identification of Trachomatous Inflammation-Follicular Using Deep Learning.

Cornea Sep 20, 2024
PURPOSE: Trachoma surveys are used to estimate the prevalence of trachomatous inflammation-follicular (TF) to guide mass antibiotic distribution. These surveys currently rely on human graders, introducing a significant resource burden and potential f...
ROC Curve Ethiopia Conjunctiva Photography Eyelids Diagnosis, Computer-Assisted Deep Learning Child, Preschool Child Trachoma Humans Neural Networks, Computer Female Infant, Newborn Reproducibility of Results Sensitivity and Specificity Male Infant Prevalence
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Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

PloS one Sep 19, 2024
Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mortality, especially in regions lacking robust medical infrastructure. In this study, we propose a comprehensive approach to extract mortality causes a...
Humans Natural Language Processing Retrospective Studies Cause of Death Prevalence Autopsy Narration Data Mining
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Prediction model for major bleeding in anticoagulated patients with cancer-associated venous thromboembolism using machine learning and natural language processing.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Sep 14, 2024
PURPOSE: We developed a predictive model to assess the risk of major bleeding (MB) within 6 months of primary venous thromboembolism (VTE) in cancer patients receiving anticoagulant treatment. We also sought to describe the prevalence and incidence o...
Spain Natural Language Processing Anticoagulants Hemorrhage Venous Thromboembolism Aged Aged, 80 and over Humans Adult Machine Learning Male Retrospective Studies Female Middle Aged Risk Assessment Neoplasms Prevalence Incidence
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Suicidal behaviors among high school graduates with preexisting mental health problems: A machine learning and GIS-based study.

The International journal of social psychiatry Sep 5, 2024
BACKGROUND: Suicidal behavior among adolescents with mental health disorders, such as depression and anxiety, is a critical issue. This study explores the prevalence and predictors of past-year suicidal behaviors among Bangladeshi high school graduat...
Humans Machine Learning Mental Disorders Female Geographic Information Systems Suicide, Attempted Adolescent Suicidal Ideation Bangladesh Risk Factors Cross-Sectional Studies Male Prevalence
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Metabolic syndrome predictive modelling in Bangladesh applying machine learning approach.

PloS one Sep 5, 2024
Metabolic syndrome (MetS) is a cluster of interconnected metabolic risk factors, including abdominal obesity, high blood pressure, and elevated fasting blood glucose levels, that result in an increased risk of heart disease and stroke. In this resear...
Young Adult Adult Male Middle Aged Prevalence Humans Machine Learning Adolescent Female Risk Factors Metabolic Syndrome Aged Obesity, Abdominal Bangladesh
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Trajectory on postpartum depression of Chinese women and the risk prediction models: A machine-learning based three-wave follow-up research.

Journal of affective disorders Aug 16, 2024
BACKGROUND: Our study delves into postpartum depression (PPD) extending observation up to six months postpartum, addressing the gap in long-term follow-ups and uncover critical intervention points.
Humans Machine Learning Pregnancy China Female Cohort Studies Follow-Up Studies East Asian People Depression, Postpartum Risk Factors Young Adult Adult Prevalence
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Gender-specific factors of suicidal ideation among high school students in Yunnan province, China: A machine learning approach.

Journal of affective disorders Aug 13, 2024
BACKGROUND: Suicidal ideation (SI) assumes a pivotal role in predicting suicidal behaviors. The incidence of SI among high (junior and senior) school students is significantly higher than that of other age groups. The aim of this study is to explore ...
Logistic Models Schools Sex Factors Humans Bullying Machine Learning Depression Female Surveys and Questionnaires Risk Factors Male Adolescent Students Suicidal Ideation Prevalence Anxiety China
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Prevalence of Avian Influenza Virus in Atypical Wild Birds Host Groups during an Outbreak of Highly Pathogenic Strain EA/AM H5N1.

Transboundary and emerging diseases Jul 29, 2024
The global outbreak of highly pathogenic avian influenza (HPAI) H5N1 Eurasian lineage goose/Guangdong clade 2.3.4.4b virus that was detected in North America in 2021 is the largest in history and has significantly impacted wild bird populations and d...
Animals Animals, Wild Disease Outbreaks Influenza A Virus, H5N1 Subtype Influenza in Birds Prevalence Birds Indiana
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Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software.

The Lancet. Digital health Jul 19, 2024
BACKGROUND: Computer-aided detection (CAD) can help identify people with active tuberculosis left undetected. However, few studies have compared the performance of commercially available CAD products for screening in high tuberculosis and high HIV se...
Mass Screening Humans South Africa Artificial Intelligence Tuberculosis Adult Prevalence Radiography, Thoracic Software Tuberculosis, Pulmonary Sensitivity and Specificity Case-Control Studies Female Male Diagnosis, Computer-Assisted Young Adult Middle Aged HIV Infections
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