AIMC Topic: Rural Population
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Real-world evaluation of RetCAD deep-learning system for the detection of referable diabetic retinopathy and age-related macular degeneration.
Clinical & experimental optometry
Aug 12, 2024
CLINICAL RELEVANCE: The challenges of establishing retinal screening programs in rural settings may be mitigated by the emergence of deep-learning systems for early disease detection.
Use of artificial intelligence-guided echocardiography to detect cardiac dysfunction and heart valve disease in rural and remote areas: Rationale and design of the AGILE-echo trial.
American heart journal
Aug 10, 2024
BACKGROUND: Transthoracic echocardiography (TTE) is essential in the diagnosis of cardiovascular diseases (CVD), including but not limited to heart failure (HF) and heart valve disease (HVD). However, its dependence on expert acquisition means that i...
A lightweight intelligent laryngeal cancer detection system for rural areas.
American journal of otolaryngology
Aug 8, 2024
OBJECTIVE: Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas. Despite existing studies on deep learning models for LC identification, challenges remain in selecting suitable models for rural areas with shortages of lary...
High-resolution mapping of essential maternal and child health service coverage in Nigeria: a machine learning approach.
BMJ open
Jun 10, 2024
BACKGROUND: National-level coverage estimates of maternal and child health (MCH) services mask district-level and community-level geographical inequities. The purpose of this study is to estimate grid-level coverage of essential MCH services in Niger...
Prevalence of non-communicable chronic diseases in rural India amongst peri- and post-menopausal women: Can artificial intelligence help in early identification?
Maturitas
May 16, 2024
AIMS: To identify peri- and post-menopausal women at risk of non-communicable diseases in rural India and to assess their prevalence amongst these groups via the use of artificial intelligence.
Leveraging AI and Machine Learning to Develop and Evaluate a Contextualized User-Friendly Cough Audio Classifier for Detecting Respiratory Diseases: Protocol for a Diagnostic Study in Rural Tanzania.
JMIR research protocols
Apr 23, 2024
BACKGROUND: Respiratory diseases, including active tuberculosis (TB), asthma, and chronic obstructive pulmonary disease (COPD), constitute substantial global health challenges, necessitating timely and accurate diagnosis for effective treatment and m...
Machine learning for predicting Chagas disease infection in rural areas of Brazil.
PLoS neglected tropical diseases
Apr 16, 2024
INTRODUCTION: Chagas disease is a severe parasitic illness that is prevalent in Latin America and often goes unaddressed. Early detection and treatment are critical in preventing the progression of the illness and its associated life-threatening comp...
Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods.
Epidemiology and health
Apr 13, 2024
OBJECTIVES: Over-the-counter (OTC) antibiotic use can cause antibiotic resistance, threatening global public health gains. To counter OTC use, this study used machine learning (ML) methods to identify predictors of OTC antibiotic use in rural Pune, I...
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
Jan 19, 2024
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...
Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity.
Accident; analysis and prevention
Dec 5, 2023
Driven by advancements in data-driven methods, recent developments in proactive crash prediction models have primarily focused on implementing machine learning and artificial intelligence. However, from a causal perspective, statistical models are pr...
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