Artículo
Improving community health-care screenings with smartphone-based AI technologies
Fecha de publicación:
05/2021
Editorial:
Elsevier
Revista:
The Lancet Digital Health
e-ISSN:
2589-7500
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Non-communicable diseases cause the majority of global disease burden and mortality. However, in both high-income countries and low-income and middle-income countries (LMICs), a substantial number of patients remain unaware that they have these life-threatening conditions. Previous studies have found that approximately half of adult diabetes cases worldwide are undetected, and a considerable proportion of patients with hypertension, lung disease, and other chronic conditions remain undiagnosed. Early screening and diagnosis are crucial to enabling prompt treatment, preventing disease progression, and reducing morbidity and mortality. However, it is challenging to screen patients who might not have access to a physician or who live in rural areas that are a considerable distance from health-care facilities. In Tanzania, more than 80% of citizens will never see a doctor in their lifetime. Even in many high-income countries such as the USA, a high proportion of the population is either uninsured or does not visit a primary care physician on a regular basis.
Palabras clave:
AL TECHNOLOGIES
,
COMMUNITY HEALTH-CARE SCREENINGS
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos(SEDE CENTRAL)
Articulos de SEDE CENTRAL
Articulos de SEDE CENTRAL
Citación
Mantena, Sreekar; Celi, Leo Anthony; Keshavjee, Salmaan; Beratarrechea, Andrea Gabriela; Improving community health-care screenings with smartphone-based AI technologies; Elsevier; The Lancet Digital Health; 3; 5; 5-2021; 280-282
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