{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T14:41:45Z","timestamp":1792593705280,"version":"4.5.0"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T00:00:00Z","timestamp":1792540800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100019725","name":"Deanship of Scientific Research, Prince Sattam bin Abdulaziz University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100019725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Surg."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Artificial intelligence (AI) is increasingly used in otolaryngology, but the extent and focus of AI research in Saudi Arabia remain unclear. This scoping review mapped the available evidence and identified key research themes and knowledge gaps.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A scoping review was conducted following the PRISMA-ScR guidelines. PubMed\/MEDLINE, Scopus, Web of Science, Google Scholar, and the Saudi Medical Journal archive were searched for studies published between January 2019 and April 2026. Eligible studies investigated AI applications or clinician perspectives within Saudi otolaryngology. The evidence was mapped across major otolaryngology domains, including cochlear implantation and hearing, rhinology and skull base surgery, facial plastic surgery, laryngology and voice, head and neck oncology, surgical and other ENT-related interventions for obstructive sleep apnoea, AI education and implementation, and AI-assisted patient education.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The searches identified 2,925 database records, four records from other sources and seven records from an updated search and expert suggestions; thirteen studies met the inclusion criteria. The evidence covered AI awareness and education, large language model (LLM)-based patient education, cochlear implantation, rhinology and skull base surgery, facial plastic surgery, laryngology and voice, and head and neck oncology; no eligible study addressed surgical or other ENT-related interventions for obstructive sleep apnoea. Clinicians were generally positive about AI, while clinical studies showed promising performance of AI models. LLM chatbots generally gave accurate postoperative advice, although, when validated tools were used, their responses were harder to read and less actionable than patient-education standards recommend. However, limited AI education, small or non-Saudi datasets, limited external validation, and implementation barriers remained important challenges.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>AI research in Saudi otolaryngology remains limited but is expanding across several clinical domains. Future research should prioritise Saudi-specific datasets, multicentre clinical validation, structured AI education, rigorous bilingual (Arabic and English) evaluation of LLM-generated patient information, and safe integration of AI into clinical practice in line with Saudi Vision 2030.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fsurg.2026.1983298","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T14:07:21Z","timestamp":1792591641000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence in Saudi otolaryngology research: a scoping review of the current landscape, gaps, and future directions"],"prefix":"10.3389","volume":"13","author":[{"given":"Turki","family":"Aldrees","sequence":"first","affiliation":[{"name":"Department of Otolaryngology, Head and Neck Surgery, College of Medicine, Prince Sattam Bin Abdulaziz University","place":["Alkharj, Saudi Arabia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdullah","family":"Alabdulqader","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology, Head and Neck Surgery, College of Medicine, Imam Mohammad Ibn Saud Islamic University","place":["Riyadh, Saudi Arabia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Al-Bar","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology, Head and Neck Surgery, College of Medicine, Imam Abdulrahman Bin Faisal University","place":["Dammam, Saudi Arabia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feras","family":"Alkholaiwi","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology, Head and Neck Surgery, College of Medicine, Imam Mohammad Ibn Saud Islamic University","place":["Riyadh, Saudi Arabia"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,21]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"baaa010","DOI":"10.1093\/database\/baaa010","article-title":"Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine","volume":"2020","author":"Ahmed","year":"2020","journal-title":"Database"},{"key":"B2","doi-asserted-by":"publisher","first-page":"118","DOI":"10.47709\/ijmdsa.v3i3.4546","article-title":"AI in healthcare: revolutionizing diagnosis and therapy","volume":"3","author":"Zeb","year":"2024","journal-title":"Int J Multidiscipl Sci Art"},{"key":"B3","first-page":"51","article-title":"Artificial intelligence for intelligent systems","volume-title":"Comprehensive Comparative Analysis of Artificial Intelligence, Machine Learning, and Deep Learning","author":"Lamaazi","year":"2024"},{"key":"B4","doi-asserted-by":"publisher","first-page":"137","DOI":"10.5742\/MEWFM.2021.94191","article-title":"Machine learning in otorhinolaryngology, head and neck surgery and its applications in diagnosis and management: undergraduates\u2019 perception toward new era","volume":"19","author":"Alomary","year":"2021","journal-title":"Middle East J Fam Med"},{"key":"B5","doi-asserted-by":"publisher","first-page":"48335","DOI":"10.1109\/ACCESS.2024.3383835","article-title":"Artificial intelligence with deep learning based automated ear infection detection","volume":"12","author":"Mehedi","year":"2024","journal-title":"IEEE Access"},{"key":"B6","doi-asserted-by":"publisher","first-page":"2309","DOI":"10.3390\/diagnostics13132309","article-title":"Diagnosis, treatment, and management of otitis media with artificial intelligence","volume":"13","author":"Ding","year":"2023","journal-title":"Diagnostics"},{"key":"B7","doi-asserted-by":"publisher","first-page":"6973","DOI":"10.3390\/jcm12226973","article-title":"Deep learning techniques and imaging in otorhinolaryngology: a state-of-the-art review","volume":"12","author":"Tsilivigkos","year":"2023","journal-title":"J Clin Med"},{"key":"B8","doi-asserted-by":"publisher","first-page":"99282","DOI":"10.1109\/ACCESS.2024.3428700","article-title":"Artificial intelligence-driven advancements in otitis media diagnosis: a systematic review","volume":"12","author":"Rony","year":"2024","journal-title":"IEEE Access"},{"key":"B9","doi-asserted-by":"publisher","first-page":"2697","DOI":"10.1007\/s00405-025-09272-5","article-title":"Artificial intelligence in otorhinolaryngology: current trends and application areas","volume":"282","author":"Demir","year":"2025","journal-title":"Eur Arch Oto-Rhino-Laryngol"},{"key":"B10","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1001\/jamaoto.2025.3911","article-title":"Deep learning in otolaryngology: a narrative review","volume":"152","author":"Novi","year":"2026","journal-title":"JAMA Otolaryngol Head Neck Surg"},{"key":"B11","doi-asserted-by":"publisher","first-page":"37","DOI":"10.53555\/AJBR.v28i4S.8237","article-title":"Artificial intelligence in Saudi healthcare: a systematic review of clinical applications supporting Vision 2030 goals","volume":"28","author":"Elrasheed","year":"2025","journal-title":"Af J Biomed Res"},{"key":"B12","doi-asserted-by":"publisher","first-page":"2449051","DOI":"10.1080\/20523211.2024.2449051","article-title":"Transforming healthcare: Saudi Arabia\u2019s Vision 2030 healthcare model","volume":"18","author":"Suleiman","year":"2025","journal-title":"J Pharm Policy Pract"},{"key":"B13","doi-asserted-by":"publisher","first-page":"1206139","DOI":"10.3389\/fdata.2023.1206139","article-title":"Artificial intelligence research strategy of the United States: critical assessment and policy recommendations","volume":"6","author":"Gursoy","year":"2023","journal-title":"Front Big Data"},{"key":"B14","doi-asserted-by":"publisher","first-page":"e70921","DOI":"10.2196\/70921","article-title":"Hype vs reality in the integration of artificial intelligence in clinical workflows","volume":"9","author":"Abd-Alrazaq","year":"2025","journal-title":"JMIR Form Res"},{"key":"B15","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1186\/s40001-025-03196-w","article-title":"Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives","volume":"30","author":"Fahim","year":"2025","journal-title":"Eur J Med Res"},{"key":"B16","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1080\/1364557032000119616","article-title":"Scoping studies: towards a methodological framework","volume":"8","author":"Arksey","year":"2005","journal-title":"Int J Soc Res Methodol"},{"key":"B17","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1186\/1748-5908-5-69","article-title":"Scoping studies: advancing the methodology","volume":"5","author":"Levac","year":"2010","journal-title":"Implement Sci"},{"key":"B18","doi-asserted-by":"publisher","first-page":"4101","DOI":"10.2147\/JMDH.S478347","article-title":"Perceptions of artificial intelligence among otolaryngologists in Saudi Arabia: a cross-sectional study","volume":"17","author":"AlSharhan","year":"2024","journal-title":"J Multidiscip Healthc"},{"key":"B19","doi-asserted-by":"publisher","first-page":"354","DOI":"10.3390\/jpm14040354","article-title":"A comprehensive evaluation of AI-assisted diagnostic tools in ENT medicine: insights and perspectives from healthcare professionals","volume":"14","author":"Alshehri","year":"2024","journal-title":"J Pers Med"},{"key":"B20","doi-asserted-by":"publisher","first-page":"2720","DOI":"10.3390\/electronics12122720","article-title":"Machine learning and cochlear implantation: predicting the post-operative electrode impedances","volume":"12","author":"Alohali","year":"2023","journal-title":"Electronics"},{"key":"B21","doi-asserted-by":"publisher","first-page":"3204","DOI":"10.3390\/su15043204","article-title":"Voice pathology detection using a two-level classifier based on combined CNN-RNN architecture","volume":"15","author":"Ksibi","year":"2023","journal-title":"Sustainability"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1177\/01455613261423741","article-title":"Diagnostic accuracy of artificial intelligence models in computed tomography interpretation of chronic rhinosinusitis: a systematic review","author":"Alanazi","year":"2026","journal-title":"Ear Nose Throat J"},{"key":"B23","doi-asserted-by":"publisher","first-page":"104267","DOI":"10.1016\/j.compbiomed.2021.104267","article-title":"Early diagnosis of thyroid cancer diseases using computational intelligence techniques: a case study of a Saudi Arabian dataset","volume":"131","author":"Olatunji","year":"2021","journal-title":"Comput Biol Med"},{"key":"B24","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1097\/SCS.0000000000010678","article-title":"Postoperative otoplasty care with ChatGPT-4: a study on artificial intelligence (AI)-assisted patient concern and education","volume":"36","author":"Albehairi","year":"2025","journal-title":"J Craniofacial Surg"},{"key":"B25","doi-asserted-by":"publisher","first-page":"2794","DOI":"10.24911\/IJMDC.51-1730291500","article-title":"The role of artificial intelligence in assisting patient education post-rhinoplasty","volume":"8","author":"Alghamdi","year":"2024","journal-title":"Int J Med Dev Ctries"},{"key":"B26","doi-asserted-by":"publisher","first-page":"1653","DOI":"10.1007\/s00266-025-05345-2","article-title":"Artificial intelligence (AI)-assisted patient education and concerns following facelift surgery: a study on ChatGPT-4 and Gemini","volume":"50","author":"Almousa","year":"2026","journal-title":"Aesthetic Plast Surg"},{"key":"B27","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1097\/SCS.0000000000011922","article-title":"Artificial intelligence in postoperative sinus care: a comparative study of ChatGPT-4, Google Gemini, and DeepSeek in patient education and support","volume":"37","author":"Alsudays","year":"2026","journal-title":"J Craniofacial Surg"},{"key":"B28","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/s00405-025-09760-8","article-title":"Comparative analysis of artificial intelligence platforms in generating post-operative instructions for endoscopic transnasal skull base surgery","volume":"283","author":"Alamri","year":"2026","journal-title":"Eur Arch Oto-Rhino-Laryngol"},{"key":"B29","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1055\/a-2719-8970","article-title":"A novel BERT-based machine learning approach for enhanced CSF leak prediction in endoscopic endonasal skull base surgery","volume":"87","author":"Alfallaj","year":"2026","journal-title":"J Neurol Surg Part B: Skull Base"},{"key":"B30","doi-asserted-by":"publisher","first-page":"2527","DOI":"10.53894\/ijirss.v8i6.10136","article-title":"Looking ahead: a systematic review of the research on AI-based applications for the deaf and hard of hearing (2000\u20132024)","volume":"8","author":"Albash","year":"2025","journal-title":"Int J Innov Res Sci Stud"},{"key":"B31","doi-asserted-by":"publisher","first-page":"12","DOI":"10.56705\/ijaimi.v2i1.135","article-title":"Exploring the acceptance of artificial intelligence in healthcare in Saudi Arabia","volume":"2","author":"Althubaiti","year":"2024","journal-title":"Int J Art Intell Med Issues"},{"key":"B32","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1002\/ohn.1080","article-title":"American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) report on artificial intelligence","volume":"172","author":"Ayoub","year":"2025","journal-title":"Otolaryngol Head Neck Surg."},{"key":"B33","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1186\/s43163-025-00927-y","article-title":"Future directions for otorhinolaryngology residency in the age of artificial intelligence: a review article","volume":"41","author":"Soliman","year":"2025","journal-title":"Egyp J Otolaryngol"},{"key":"B34","doi-asserted-by":"publisher","first-page":"20552076251396981","DOI":"10.1177\/20552076251396981","article-title":"Bridging the AI implementation gap in otolaryngology: a clinical commentary","volume":"11","author":"Burmeister","year":"2025","journal-title":"Digit Health"},{"key":"B35","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1002\/ohn.70285","article-title":"Clinical applications of multimodal artificial intelligence in otolaryngology: a state-of-the-art review","volume":"175","author":"Li","year":"2026","journal-title":"Otolaryngol Head Neck Surg."},{"key":"B36","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1186\/s43163-026-01169-2","article-title":"Artificial intelligence in otorhinolaryngology: a scoping review of diagnostic, surgical, and rehabilitative applications","volume":"42","author":"Lin","year":"2026","journal-title":"Egyp J Otolaryngol"},{"key":"B37","doi-asserted-by":"publisher","first-page":"e70433","DOI":"10.1002\/lio2.70433","article-title":"Diagnostic performance of a large language model (ChatGPT-4o) in chronic rhinosinusitis CT scan interpretation","volume":"11","author":"Alsayyari","year":"2026","journal-title":"Laryngoscope Investig Otolaryngol"},{"key":"B38","volume-title":"Guidance on Artificial Intelligence (AI) and Machine Learning (ML) Technologies Based Medical Devices (MDS-G010)","year":"2023"},{"key":"B39","volume-title":"AI Ethics Principles, Version 1.0","year":"2023"},{"key":"B40","doi-asserted-by":"publisher","first-page":"e46454","DOI":"10.7759\/cureus.46454","article-title":"A systematic review of the barriers to the implementation of artificial intelligence in healthcare","volume":"15","author":"Ahmed","year":"2023","journal-title":"Cureus"},{"key":"B41","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1186\/s43163-025-00935-y","article-title":"Artificial intelligence (AI) in ORL: pitfalls and challenges","volume":"41","author":"El-Anwar","year":"2025","journal-title":"Egyp J Otolaryngol"}],"container-title":["Frontiers in Surgery"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fsurg.2026.1983298\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T14:07:23Z","timestamp":1792591643000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fsurg.2026.1983298\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,21]]},"references-count":41,"alternative-id":["10.3389\/fsurg.2026.1983298"],"URL":"https:\/\/doi.org\/10.3389\/fsurg.2026.1983298","relation":{},"ISSN":["2296-875X"],"issn-type":[{"value":"2296-875X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,21]]},"article-number":"1983298"}}