ArticleDiagnostics (Basel, Switzerland)2023
A Machine Learning Approach to Assess Patients with Deep Neck Infection Progression to Descending Mediastinitis: Preliminary Results.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Recognizing Descending Necrotizing Mediastinitis in Adults: A Narrative Review of Diagnostic Dilemmas and Barriers.Cureus · 2026Review
- Deep Neck Infections: The Effectiveness of Therapeutic Management and Bacteriological Profile.Medicina (Kaunas, Lithuania) · 2025Observational
- An introduction to machine learning and generative artificial intelligence for otolaryngologists-head and neck surgeons: a narrative review.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDeep neck infection (DNI) is a serious infectious disease, and descending mediastinitis is a fatal infection of the mediastinum. However, no study has applied artificial intelligence to assess progression to descending mediastinitis in DNI patients. Thus, we developed a model to assess the possible progression of DNI to descending mediastinitis.
methodsBetween August 2017 and December 2022, 380 patients with DNI were enrolled; 75% of patients (
resultsIn the training and test groups, there was no statistical significance (all
conclusionsOur model can assess the progression of DNI to descending mediastinitis depending on clinical and imaging parameters. It can be used to identify DNI patients who will benefit from prompt treatment.
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