{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T09:12:30Z","timestamp":1778836350814,"version":"3.51.4"},"reference-count":12,"publisher":"Index Copernicus","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Otolaryngol Pol"],"published-print":{"date-parts":[[2026,5,7]]},"abstract":"<p><strong>Introduction:<\/strong> Extranodal natural killer\/T-cell lymphoma, nasal type (ENKTL), is a rare&nbsp;EBV-associated malignancy characterized by destructive tumors in the nasal cavity,&nbsp;often causing delayed diagnosis due to tissue necrosis. Artificial intelligence (AI) has&nbsp;the potential to assist in complex diagnostic challenges.<br \/><strong>Aim: <\/strong>This study aimed to evaluate the diagnostic performance and clinical relevance&nbsp;of publicly accessible AI-driven platforms in identifying ENKTL based on a real,&nbsp;challenging clinical case.<br \/><strong>Materials and methods: <\/strong>Clinical data from a 26-year-old male patient with protracted&nbsp;and complicated symptoms initially suggesting infectious conditions were used. Eight AI symptom assessment platforms were tested for diagnostic outputs using identical&nbsp;anonymized case inputs at early and advanced disease stages. Diagnostic suggestions,&nbsp;alignment with the final histopathological diagnosis, and quality of recommendations&nbsp;were analyzed.<br \/><strong>Results: <\/strong>Six of eight platforms provided valid differential diagnoses consistent with&nbsp;clinical data. Early-stage data mainly generated infectious diagnoses such as peritonsillar&nbsp;abscess. Advanced-stage data shifted diagnoses toward invasive fungal, autoimmune,&nbsp;and malignant diseases, with platforms such as Doctronic and Symptomate&nbsp;explicitly including lymphoma. Diagnostic pathways varied, with recommendations for&nbsp;comprehensive laboratory tests, imaging, biopsies, and immunological assays. AI systems&nbsp;demonstrated oncologic vigilance when EBV viral data were included, emphasizing&nbsp;clinician oversight for accurate diagnosis.<br \/><strong>Conclusions:<\/strong> AI-based diagnostic platforms show promise in supporting preliminary&nbsp;assessment and differential diagnosis in rare, complex cases such as ENKTL. While AI&nbsp;can guide diagnostic reasoning and propose investigations, it does not replace clinical&nbsp;judgment. Further development and validation of AI tools are needed to enhance their&nbsp;reliability and integration into medical practice.<\/p><\/ns3:p>","DOI":"10.5604\/01.3001.0055.7287","type":"journal-article","created":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T10:53:04Z","timestamp":1776941584000},"page":"39-45","source":"Crossref","is-referenced-by-count":0,"title":["The Role of Artificial Intelligence Algorithms in Challenging Diagnostic Cases \u2013 Between Potential and Real Clinical Support"],"prefix":"10.5604","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2989-3927","authenticated-orcid":false,"given":"Agata","family":"Doligalska-Dolina","sequence":"first","affiliation":[{"name":"Department of Otolaryngology and Laryngological Oncology, Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Klaudia","family":"Zi\u00f3\u0142kowska","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology and Laryngological Oncology, Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1865-2122","authenticated-orcid":false,"given":"Maciej J.","family":"Wr\u00f3bel","sequence":"additional","affiliation":[{"name":"Department of Otolaryngology and Laryngological Oncology, Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"3689","reference":[{"key":"638433r1","doi-asserted-by":"crossref","unstructured":"Kimura H., de Leval L., Cai Q., Kim W.S.: EBV-associated NK and T-cell lymphoidneoplasms. 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