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Identifying developments over a decade in the digital health and telemedicine landscape in the UK using quantitative text mining.
Geifman, Nophar; Armes, Jo; Whetton, Anthony D.
  • Geifman N; School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
  • Armes J; School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
  • Whetton AD; School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.
Front Digit Health ; 5: 1092008, 2023.
Artículo en Inglés | MEDLINE | ID: covidwho-2314791
ABSTRACT
The use of technologies that provide objective, digital data to clinicians, carers, and service users to improve care and outcomes comes under the unifying term Digital Health. This field, which includes the use of high-tech health devices, telemedicine and health analytics has, in recent years, seen significant growth in the United Kingdom and worldwide. It is clearly acknowledged by multiple stakeholders that digital health innovations are necessary for the future of improved and more economic healthcare service delivery. Here we consider digital health-related research and applications by using an informatics tool to objectively survey the field. We have used a quantitative text-mining technique, applied to published works in the field of digital health, to capture and analyse key approaches taken and the diseases areas where these have been applied. Key areas of research and application are shown to be cardiovascular, stroke, and hypertension; although the range seen is wide. We consider advances in digital health and telemedicine in light of the COVID-19 pandemic.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio observacional Idioma: Inglés Revista: Front Digit Health Año: 2023 Tipo del documento: Artículo País de afiliación: Fdgth.2023.1092008

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio observacional Idioma: Inglés Revista: Front Digit Health Año: 2023 Tipo del documento: Artículo País de afiliación: Fdgth.2023.1092008