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Medical doctor's perception of artificial intelligence during the COVID-19 era: A mixed methods study.
Dongre, Ashwini S; More, Sandeep D; Wilson, Vidhya; Singh, R Jai.
Afiliación
  • Dongre AS; Department of Community Medicine, Government Medical College, Gondia, Maharashtra, India.
  • More SD; Department of Neurosurgery, Rajiv Gandhi Institute of Medical Sciences, Adilabad, Telangana State, India.
  • Wilson V; Department of Community Medicine, Rajiv Gandhi Institute of Medical Sciences, Adilabad, Telangana State, India.
  • Singh RJ; Department of Orthopaedics, Rajiv Gandhi Institute of Medical Sciences, Adilabad, Telangana State, India.
J Family Med Prim Care ; 13(5): 1931-1936, 2024 May.
Article en En | MEDLINE | ID: mdl-38948570
ABSTRACT

Background:

Artificial intelligence (AI) has led to the development of various opportunities during the COVID-19 pandemic. An abundant number of applications have surfaced responding to the pandemic, while some other applications were futile.

Objectives:

The present study aimed to assess the perception and opportunities of AI used during the COVID-19 pandemic and to explore the perception of medical data analysts about the inclusion of AI in medical education. Material and

Methods:

This study adopted a mixed-method research design conducted among medical doctors for the quantitative part while including medical data analysts for the qualitative interview.

Results:

The study reveals that nearly 64.8% of professionals were working in high COVID-19 patient-load settings and had significantly more acceptance of AI tools compared to others (P < 0.05). The learning barrier like engaging in new skills and working under a non-medical hierarchy led to dissatisfaction among medical data analysts. There was widespread recognition of their work after the COVID-19 pandemic.

Conclusion:

Notwithstanding that the majority of professionals are aware that public health emergency creates a significant strain on doctors, the majority still have to work in extremely high case load setting to demand solutions. AI applications are still not being integrated into medicine as fast as technology has been advancing. Sensitization workshops can be conducted among specialists to develop interest which will encourage them to identify problem statements in their fields, and along with AI experts, they can create AI-enabled algorithms to address the problems. A lack of educational opportunities about AI in formal medical curriculum was identified.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Family Med Prim Care Año: 2024 Tipo del documento: Article País de afiliación: India Pais de publicación: India
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Family Med Prim Care Año: 2024 Tipo del documento: Article País de afiliación: India Pais de publicación: India