AIMC Topic: Facial Nerve Injuries

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Prediction of facial nerve outcomes after surgery for vestibular schwannoma using machine learning-based models: a systematic review and meta-analysis.

Neurosurgical review
Postoperative facial nerve (FN) dysfunction is associated with a significant impact on the quality of life of patients and can result in psychological stress and disorders such as depression and social isolation. Preoperative prediction of FN outcome...

Development and application of explainable artificial intelligence using machine learning classification for long-term facial nerve function after vestibular schwannoma surgery.

Journal of neuro-oncology
PURPOSE: Vestibular schwannomas (VSs) represent the most common cerebellopontine angle tumors, posing a challenge in preserving facial nerve (FN) function during surgery. We employed the Extreme Gradient Boosting machine learning classifier to predic...

A multi-institutional machine learning algorithm for prognosticating facial nerve injury following microsurgical resection of vestibular schwannoma.

Scientific reports
Vestibular schwannomas (VS) are the most common tumor of the skull base with available treatment options that carry a risk of iatrogenic injury to the facial nerve, which can significantly impact patients' quality of life. As facial nerve outcomes re...

Machine Learning Models for Predicting Facial Nerve Palsy in Parotid Gland Surgery for Benign Tumors.

The Journal of surgical research
BACKGROUND: Despite the increasing use of intraoperative facial nerve monitoring during parotid gland surgery (PGS) and the improvement in the preoperative radiological assessment, facial nerve injury (FNI) remains the most severe complication after ...