Machine learning for functional outcome prediction after vestibular schwannoma surgery: a systematic review and diagnostic test accuracy meta-analysis
Shiva A Nischal, Shaan Patel, Musa China, Kush M Kale, Yi Hein Chai, Santosh Guru, William R Muirhead, Patrick Grover · 2026
Read Machine learning for functional outcome prediction after vestibular schwannoma surgery: a systematic review and diagnostic test accuracy meta-analysis by Shiva A Nischal, Shaan Patel, Musa China, Kush M Kale, Yi Hein Chai, Santosh Guru, William R Muirhead, Patrick Grover (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13503505.txt.
Description
Shiva Nischal and co-authors review machine learning tools that predict recovery after brain tumor surgery in a 2026 analysis. The tumors, called vestibular schwannomas, grow on the hearing nerve. Surgery can cost patients facial movement or hearing. Models that forecast those outcomes could guide consent and planning. The team searched three databases for studies that used learning models for this task and pooled their accuracy.
Ten studies with about twelve hundred seventy patients and fifty six models qualified. The best model from each study scored high on sorting patients: strong marks for both facial nerve outcomes and hearing preservation. Pooling every model on held out data gave lower, more sober scores. Tumor size, age, tumor position, and starting hearing were the most common strong predictors. The authors warn that most studies carried unclear or high bias risk, so clinical use needs better validation.
Catalog record
| CREATOR | Shiva A Nischal, Shaan Patel, Musa China, Kush M Kale, Yi Hein Chai, Santosh Guru, William R Muirhead, Patrick Grover |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |