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August 7, 2024Clinical OtolaryngologyOpen Access

Machine Learning Model Predicts Postoperative Outcomes in Chronic Rhinosinusitis With Nasal Polyps

Anda Gâta Lajos Ráduly Liviuţa Budişan Adél Bajcsi Teodora‐Maria Ursu Camelia Chira Laura Dioşan Ioana Berindan‐Neagoe Silviu Albu

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Abstract

Evaluating the possibility of predicting chronic rhinosinusitis with nasal polyps (CRSwNP) disease course using Artificial Intelligence.

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Cite This Study

Gâta et al. (2024) studied this question.

synapsesocial.com/papers/68e5d246b6db64358756825f https://doi.org/10.1111/coa.14208

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Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1[Exploration of prognostic models for chronic rhinosinusitis with nasal polyps based on machine learning].2024 · 1 citations
2The Usefulness of Machine Learning Models to Predict Patient‐Reported Outcome Measures in Chronic Rhinosinusitis With Nasal PolypsOriginal Research · 2026
3Development and Interpretation of a Machine Learning-Based Predictive Model Using Clinical Parameters for Eosinophilic Chronic Rhinosinusitis With Nasal PolypsOriginal Research · 2026 · 2 citations
4Development of an AI-based algorithm for the identification, segmentation, and classification of chronic Rhinosinusitis (CRS)2024
5Machine Learning‐Based Predictive Modeling for the Development of Chronic Rhinosinusitis Using Longitudinal Health RecordsOriginal Research · 2026