ArticleJournal of clinical medicine2022
Towards a Reliable and Rapid Automated Grading System in Facial Palsy Patients: Facial Palsy Surgery Meets Computer Science.
Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Resource utilization and outcomes of inpatient eyelid reconstruction in facial palsy patients: A 20-year HCUP-NIS study.JPRAS open · 2026Article
- Rewiring faces: advances and outcomes in facial nerve reconstruction after facial vascularized composite allotransplantation.Frontiers in surgery · 2026Review
- Continuous and componentized facial palsy measurement alignment and clinical interpretable model.NPJ digital medicine · 2025Article
- Are ChatGPT's Answers to Questions About Salivary Gland Diseases Accurate and Reliable?Turkish archives of otorhinolaryngology · 2025Article
- Diagnosing facial synkinesis using artificial intelligence to advance facial palsy care.Scientific reports · 2025Article
- Turn Your Vision into Reality-AI-Powered Pre-operative Outcome Simulation in Rhinoplasty Surgery.Aesthetic plastic surgery · 2024Article
- Artificial intelligence in plastic surgery, where do we stand?JPRAS open · 2024Review
- Truth Lies in the Depths: Novel Insights into Facial Aesthetic Measurements from a U.S. Survey Panel.Aesthetic plastic surgery · 2024Article
- ChatGPT vs UpToDate: comparative study of usefulness and reliability of Chatbot in common clinical presentations of otorhinolaryngology-head and neck surgery.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 · 2024Article
- Pure Wisdom or Potemkin Villages? A Comparison of ChatGPT 3.5 and ChatGPT 4 on USMLE Step 3 Style Questions: Quantitative Analysis.JMIR medical education · 2024Article
- The law code of ChatGPT and artificial intelligence-how to shield plastic surgeons and reconstructive surgeons against Justitia's sword.Frontiers in surgery · 2024Article
- Diagnosing lagophthalmos using artificial intelligence.Scientific reports · 2023Article
- A Narrative Review of Artificial Intelligence (AI) for Objective Assessment of Aesthetic Endpoints in Plastic Surgery.Aesthetic plastic surgery · 2023Review
- Face the Future-Artificial Intelligence in Oral and Maxillofacial Surgery.Journal of clinical medicine · 2023Review
- ChatGPT's quiz skills in different otolaryngology subspecialties: an analysis of 2576 single-choice and multiple-choice board certification preparation questions.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 · 2023Article
- Histomorphometry of the Sural Nerve for Use as a CFNG in Facial Reanimation Procedures.Journal of clinical medicine · 2023Article
- DeepSmile: Anomaly Detection Software for Facial Movement Assessment.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundReliable, time- and cost-effective, and clinician-friendly diagnostic tools are cornerstones in facial palsy (FP) patient management. Different automated FP grading systems have been developed but revealed persisting downsides such as insufficient accuracy and cost-intensive hardware. We aimed to overcome these barriers and programmed an automated grading system for FP patients utilizing the House and Brackmann scale (HBS).
methodsImage datasets of 86 patients seen at the Department of Plastic, Hand, and Reconstructive Surgery at the University Hospital Regensburg, Germany, between June 2017 and May 2021, were used to train the neural network and evaluate its accuracy. Nine facial poses per patient were analyzed by the algorithm.
resultsThe algorithm showed an accuracy of 100%. Oversampling did not result in altered outcomes, while the direct form displayed superior accuracy levels when compared to the modular classification form (n = 86; 100% vs. 99%). The Early Fusion technique was linked to improved accuracy outcomes in comparison to the Late Fusion and sequential method (n = 86; 100% vs. 96% vs. 97%).
conclusionsOur automated FP grading system combines high-level accuracy with cost- and time-effectiveness. Our algorithm may accelerate the grading process in FP patients and facilitate the FP surgeon's workflow.
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