Development and application of explainable artificial intelligence using machine learning classification for long-term facial nerve function after vestibular schwannoma surgery
We introduce an effective ML model for classifying long-term FN outcomes following VS surgery. Short-term FN function was identified as the key predictor of long-term function. This model's excellent ability to differentiate bad and good outcomes makes it useful for evaluating patients and providing recommendations regarding FN dysfunction management.
Authors
- Sławomir Kujawski (ORCID: https://orcid.org/0000-0001-5186-5037)
- Edyta Maj (ORCID: https://orcid.org/0000-0003-4648-6942)
- Andrzej Marchel (ORCID: https://orcid.org/0000-0002-1521-6408)
- Łukasz Przepiórka (ORCID: https://orcid.org/0000-0002-2877-0475)
- Przemysław Kunert (ORCID: https://orcid.org/0000-0002-0583-9505)
- Katarzyna Wójtowicz
Institutions
- Medical University of Warsaw (PL)
- Nicolaus Copernicus University (PL)
- Collegium Medicum in Bydgoszcz (PL)
Publication Details
- Journal
- Journal of Neuro-Oncology
- Published
- 2024-10-11
- DOI
- https://doi.org/10.1007/s11060-024-04844-7
- Citations
- 8
- Primary Topic
- Meningioma and schwannoma management
- Type
- article
- Field-Weighted Citation Impact
- 3.09