ArticleJournal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
The Utilization of Artificial Intelligence by Pediatric Otolaryngology Surgeons in Professional Practice.
Article in Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
8 authors.
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Abstract
ImportanceThe role of artificial intelligence (AI) within medicine has increased exponentially over the last decade. However, adoption across medical specialties remains variable, influenced by institutional support, availability of tools, and concerns about accuracy, privacy, and legal liability. Addressing these barriers is necessary to achieving the full clinical capacity of AI.ObjectivesThis study aimed to explore current AI usage patterns among pediatric otolaryngologists and highlight perceived benefits and barriers to adoption.DesignCross-sectional survey design.SettingAll aspects of the present study were conducted remotely, with the survey link being distributed within a private group chat.ParticipantsParticipants were recruited via an international pediatric otolaryngology WhatsApp group chat. Admission is through invitation only.Intervention or ExposuresThe survey sought to characterize a variety of themes regarding AI, including utilization patterns, attitudes, motivational factors and barriers to adoption, and extent of institutional support.Main Outcome MeasuresResponses were evaluated using chi-squared tests and descriptive statistics.ResultsSurvey responses were analyzed from 50 individuals, reflecting a response rate of 15.2%. More than half of survey respondents (60.9%, n = 28/46) use AI in practice, relying on tools like ChatGPT, iScribe, and Gemini to improve workplace efficiency (71.4%, n = 20/28) and address administrative burdens (64.2%, n = 18/28). Despite current adoption of AI, participants identified a lack of institutional guidelines (66.7%, n = 30/45) and support (54.3%, n = 25/47) as major barriers to widespread integration across the subspecialty. No statistically-significant association was found between age and likelihood of AI adoption (
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