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Artificial intelligence in medicine: A comprehensive survey of medical doctor’s perspectives in Portugal

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  • Ana Rita Pedro
  • Michelle B Dias
  • Liliana Laranjo
  • Ana Soraia Cunha
  • João V Cordeiro

Abstract

Artificial Intelligence (AI) is increasingly influential across various sectors, including healthcare, with the potential to revolutionize clinical practice. However, risks associated with AI adoption in medicine have also been identified. Despite the general understanding that AI will impact healthcare, studies that assess the perceptions of medical doctors about AI use in medicine are still scarce. We set out to survey the medical doctors licensed to practice medicine in Portugal about the impact, advantages, and disadvantages of AI adoption in clinical practice. We designed an observational, descriptive, cross-sectional study with a quantitative approach and developed an online survey which addressed the following aspects: impact on healthcare quality of the extraction and processing of health data via AI; delegation of clinical procedures on AI tools; perception of the impact of AI in clinical practice; perceived advantages of using AI in clinical practice; perceived disadvantages of using AI in clinical practice and predisposition to adopt AI in professional activity. Our sample was also subject to demographic, professional and digital use and proficiency characterization. We obtained 1013 valid, fully answered questionnaires (sample representativeness of 99%, confidence level (p

Suggested Citation

  • Ana Rita Pedro & Michelle B Dias & Liliana Laranjo & Ana Soraia Cunha & João V Cordeiro, 2023. "Artificial intelligence in medicine: A comprehensive survey of medical doctor’s perspectives in Portugal," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-24, September.
    • Handle: RePEc:plo:pone00:0290613
    DOI: 10.1371/journal.pone.0290613
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    References listed on IDEAS

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    1. Wenjuan Fan & Jingnan Liu & Shuwan Zhu & Panos M. Pardalos, 2020. "Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS)," Annals of Operations Research, Springer, vol. 294(1), pages 567-592, November.
    2. Leonard Feldt, 1980. "A test of the hypothesis that Cronbach's alpha reliability coefficient is the same for two tests administered to the same sample," Psychometrika, Springer;The Psychometric Society, vol. 45(1), pages 99-105, March.
    3. Heba Edrees & Wenyu Song & Ania Syrowatka & Aurélien Simona & Mary G. Amato & David W. Bates, 2022. "Intelligent Telehealth in Pharmacovigilance: A Future Perspective," Drug Safety, Springer, vol. 45(5), pages 449-458, May.
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