Examining Diagnostic Errors in the Field of Otorhinolaryngology within the Challenging Landscape of Limited-Resource Healthcare

Gangil, Tarun; Rao, Divya

doi:10.1007/s12070-024-04490-5

Cited by 1 publication

(1 citation statement)

References 34 publications

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“…The assessment of the clinical impact and accuracy of AI-assisted diagnostics in ENT practice revealed promising results, corroborating previous research findings in the field. Our study demonstrated a favorable perception among respondents regarding the accuracy and effectiveness of AI tools in diagnosing ENT conditions, aligning with studies by Gangil et al [26] and Winter et al [27], have highlighted the potential of AI to improve diagnostic outcomes in various medical specialties, including ENT. The perceived benefits of AI in enhancing diagnostic efficiency and accuracy were further supported by findings from a systematic review by Yin et al [28], which showed that AI-based diagnostic systems consistently outperformed traditional methods in terms of diagnostic accuracy and speed [28].…”

Section: Discussionsupporting

confidence: 88%

A Comprehensive Evaluation of AI-Assisted Diagnostic Tools in ENT Medicine: Insights and Perspectives from Healthcare Professionals

Alshehri,

Alahmari,

Alasiry

2024

JPM

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The integration of Artificial Intelligence (AI) into healthcare has the potential to revolutionize medical diagnostics, particularly in specialized fields such as Ear, Nose, and Throat (ENT) medicine. However, the successful adoption of AI-assisted diagnostic tools in ENT practice depends on the understanding of various factors; these include influences on their effectiveness and acceptance among healthcare professionals. This cross-sectional study aimed to assess the usability and integration of AI tools in ENT practice, determine the clinical impact and accuracy of AI-assisted diagnostics in ENT, measure the trust and confidence of ENT professionals in AI tools, gauge the overall satisfaction and outlook on the future of AI in ENT diagnostics, and identify challenges, limitations, and areas for improvement in AI-assisted ENT diagnostics. A structured online questionnaire was distributed to 600 certified ENT professionals with at least one year of experience in the field. The questionnaire assessed participants’ familiarity with AI tools, usability, clinical impact, trust, satisfaction, and identified challenges. A total of 458 respondents completed the questionnaire, resulting in a response rate of 91.7%. The majority of respondents reported familiarity with AI tools (60.7%) and perceived them as generally usable and clinically impactful. However, challenges such as integration with existing systems, user-friendliness, accuracy, and cost were identified. Trust and satisfaction levels varied among participants, with concerns regarding data privacy and support. Geographic and practice setting differences influenced perceptions and experiences. The study highlights the diverse perceptions and experiences of ENT professionals regarding AI-assisted diagnostics. While there is general enthusiasm for these tools, challenges related to integration, usability, trust, and cost need to be addressed for their widespread adoption. These findings provide valuable insights for developers, policymakers, and healthcare providers aiming to enhance the role of AI in ENT practice.

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