AIMC Topic: Prevalence

Clear Filters Showing 71 to 80 of 280 articles

Predicting Homelessness Among Transitioning U.S. Army Soldiers.

American journal of preventive medicine
INTRODUCTION: This study develops a practical method to triage Army transitioning service members (TSMs) at highest risk of homelessness to target a preventive intervention.

Prevalence and Correlates of Vitamin D Deficiency among Adult Population in Urban and Rural Areas of the National Capital Region of Delhi, India.

WHO South-East Asia journal of public health
High prevalence of Vitamin D deficiency has been reported among selective population, but its population prevalence from representative adult population is lacking in India. The aim of this study was to estimate the prevalence and identify the correl...

Prevalence of chronic kidney disease and metabolic related indicators in Mianzhu, Sichuan, China.

Frontiers in public health
BACKGROUND: Chronic kidney disease (CKD) is a major public health problem worldwide. Periodic surveys are essential for monitoring the prevalence of CKD and its risk factors. We assessed the prevalence of CKD and its risk factors in Mianzhu City in 2...

Applying data science methodologies with artificial intelligence variant reinterpretation to map and estimate genetic disorder prevalence utilizing clinical data.

American journal of medical genetics. Part A
Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patient encounters. Genetic variants from all genetic testing resulting to a large pediatric healthcare sy...

Prevalence of JC Polyomavirus in Patients with Neuroinvasive Disease of Unknown Etiology in Croatia.

Medicina (Kaunas, Lithuania)
: John Cunningham polyomavirus (JCPyV) is a highly prevalent virus in the human population. The prevalence of JCPyV in patients with central nervous system disorders has not been examined extensively. The aim of this study was to analyze the prevalen...

Population-Based Artificial Intelligence Assessment of Relationship Between the Risk Factors for Diabetic Retinopathy in Indian Population.

Ophthalmic epidemiology
PURPOSE: Risk factors (RFs), like 'body mass index (BMI),' 'age,' and 'gender' correlate with Diabetic Retinopathy (DR) diagnosis and have been widely studied. This study examines how these three secondary RFs independently affect the predictive capa...

Natural language processing diagnosed behavioural disturbance phenotypes in the intensive care unit: characteristics, prevalence, trajectory, treatment, and outcomes.

Critical care (London, England)
BACKGROUND: Natural language processing (NLP) may help evaluate the characteristics, prevalence, trajectory, treatment, and outcomes of behavioural disturbance phenotypes in critically ill patients.

An interpretable machine learning model of cross-sectional U.S. county-level obesity prevalence using explainable artificial intelligence.

PloS one
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
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...