Artificial intelligence, deep learning, radiomics, computational pathology, large language models and signal processing in rhinology.
16 tracked publications · last updated 2026-06-04
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Publications
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Impact of real-world confounders on the accuracy of an AI model to support read out of skin prick automated test results
Roux K et al. — Rhinology (2026-06) · Original
Evaluates how real-world confounders affect an AI model reading automated skin-prick (S.P.A.T.) test results.
PubMed · DOI · PMID 42233219 -
Comment on ‘Evaluating the efficacy and readability of advanced large language models in responding to patients’ frequently asked questions about chronic rhinosinusitis: a comparative analysis’
Sivri I et al. — Eur Arch Otorhinolaryngol (2026-06) · Letter
Correspondence on a study of large-language-model efficacy and readability for CRS patient FAQs.
PubMed · DOI · PMID 42228121 -
AI-Based Quantitative Nasal Cytology for Predicting Eosinophilic Chronic Rhinosinusitis With Nasal Polyps: A Pilot Study
Li J et al. — Int Forum Allergy Rhinol (2026-06) · Original
Pilot AI model using quantitative nasal cytology to predict eosinophilic CRSwNP.
PubMed · DOI · PMID 42223912 -
Evaluating large language models in chronic rhinosinusitis: methodological constraints and the need for clinically grounded validation
Tahir HN et al. — Eur Arch Otorhinolaryngol (2026-06) · Letter
Commentary arguing that large-language-model evaluations in CRS require clinically grounded validation.
PubMed · DOI · PMID 42223621 -
Assessment system for short-term lower cranial nerve dysfunction following medulla oblongata glioma surgery: risk stratification and optimal surgical strategy
Zhang M et al. — J Neurosurg (2026-05) · Original
Machine-learning predictive model (with SHAP and nomogram) for lower-cranial-nerve dysfunction after medullary glioma resection to guide extent-of-resection decisions.
PubMed · DOI · PMID 42214095 -
Explainable hybrid CNN-transformer with self-supervised learning for structural analysis of paranasal sinus CT
Ullah N et al. — Front Comput Neurosci (2026-05) · Original
Self-supervised, explainable CNN-transformer segments the four paranasal sinuses and flags structural anomalies on multi-institutional CT without pathology labels.
PubMed · DOI · PMID 42211246 -
Automated Classification of Maxillary Sinus Ostium Patency Using a ConvNeXt-Tiny + DeiT Gated MLP-Based Hybrid Deep Learning Model: A Retrospective CBCT Study
Talo F et al. — Diagnostics (Basel) (2026-05) · Original
Hybrid CNN-transformer model with gated fusion classifies maxillary sinus ostium patency on CBCT.
PubMed · DOI · PMID 42196878 -
Detection of maxillary sinusitis of endodontic origin in cone-beam CT images using deep learning algorithms
Sherif OAS et al. — Sci Rep (2026-05) · Original
Deep-learning pipeline (anatomic classifier, segmenter, multi-view classifier) distinguishes normal sinus, endodontic, and non-endodontic maxillary sinusitis on CBCT.
PubMed · DOI · PMID 42192120 -
Sinonasal outcomes on nasal acoustics and resonance (SONAR)
Berick N et al. — Rhinology (2026-06) · Original
Mel-frequency cepstral coefficients/spectral analysis detect post-FESS resonance changes missed by conventional acoustic measures.
PubMed · DOI · PMID 41487079 -
CT-override: endoscopic updates to preoperative anatomical models during ablative surgery
Mangulabnan JE et al. (Johns Hopkins) — Int J Comput Assist Radiol Surg (2026-06) · Original
Fuses preoperative CT with endoscopic video via signed-distance fields for dynamic, submillimeter intraoperative model updates — a step toward fully vision-guided sinus navigation.
PubMed · DOI · PMID 42230859 -
Explainable AI predicts inflammatory and spatial heterogeneity from nasal polyp histology
Wang K et al. — J Allergy Clin Immunol (2025-09) · Original
Explainable computational pathology on nasal polyp histology to predict inflammatory and spatial heterogeneity.
PubMed · DOI · PMID 40902945 -
Proteomic profiling and machine learning for endotype prediction in chronic rhinosinusitis
Morgenstern C et al. — J Allergy Clin Immunol (2025-09) · Original
Machine learning on nasal proteomics to predict CRS endotype.
PubMed · DOI · PMID 40939758 -
Recurrence of CRSwNP After Surgery: Risk Factors, Predictive Models, and More
Chen YS et al. — Medicina (Kaunas) (2025-09) · Review
Review of risk factors and predictive (incl. ML) models for CRSwNP recurrence after surgery.
PubMed · DOI · PMID 41011011 -
Artificial Intelligence in Rhinology
Bayar Muluk N et al. — J Craniofac Surg (2025-07) · Review
Narrative review mapping AI applications across rhinology — diagnosis, imaging interpretation and workflow.
PubMed · DOI · PMID 40608779 -
Artificial intelligence-assisted detection of nasopharyngeal carcinoma
Shi Y et al. — Lancet Digit Health (2025-06) · Multicenter / Validation
Multicenter validation of an AI model for nasopharyngeal carcinoma detection.
PubMed · DOI · PMID 40544083 -
Leveraging Large Language Models to Enhance Patient Educational Resources in Rhinology
Shaari AL et al. — Ann Otol Rhinol Laryngol (2025-05) · Original
LLMs used to improve readability/quality of rhinology patient-education materials.
PubMed · DOI · PMID 40437711
Sources indexed via PubMed (NCBI). Each entry links to its PubMed record and DOI.