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Artificial intelligence-enhanced patient evaluation: bridging art and science.
Oikonomou, Evangelos K; Khera, Rohan.
Afiliação
  • Oikonomou EK; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, 333 Cedar Street, PO Box 208017, New Haven, 06520-8017 CT, USA.
  • Khera R; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, 333 Cedar Street, PO Box 208017, New Haven, 06520-8017 CT, USA.
Eur Heart J ; 2024 Jul 08.
Article em En | MEDLINE | ID: mdl-38976371
ABSTRACT
The advent of digital health and artificial intelligence (AI) has promised to revolutionize clinical care, but real-world patient evaluation has yet to witness transformative changes. As history taking and physical examination continue to rely on long-established practices, a growing pipeline of AI-enhanced digital tools may soon augment the traditional clinical encounter into a data-driven process. This article presents an evidence-backed vision of how promising AI applications may enhance traditional practices, streamlining tedious tasks while elevating diverse data sources, including AI-enabled stethoscopes, cameras, and wearable sensors, to platforms for personalized medicine and efficient care delivery. Through the lens of traditional patient evaluation, we illustrate how digital technologies may soon be interwoven into routine clinical workflows, introducing a novel paradigm of longitudinal monitoring. Finally, we provide a skeptic's view on the practical, ethical, and regulatory challenges that limit the uptake of such technologies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Eur Heart J Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Eur Heart J Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos