Application of an artificial neural network model for early outcome prediction of gamma knife radiosurgery in patients with trigeminal neuralgia and determining the relative importance of risk factors.
Journal:
Clinical neurology and neurosurgery
PMID:
30825722
Abstract
OBJECTIVES: Stereotactic radiosurgery (SRS) is a minimally invasive modality for the treatment of trigeminal neuralgia (TN). Outcome prediction of this modality is very important for proper case selection. The aim of this study was to create artificial neural networks (ANN) to predict the clinical outcomes after gamma knife radiosurgery (GKRS) in patients with TN, based on preoperative clinical factors.
Authors
Keywords
Adolescent
Adult
Aged
Aged, 80 and over
Depression
Diabetes Mellitus
Female
Follow-Up Studies
Humans
Kaplan-Meier Estimate
Male
Middle Aged
Neural Networks, Computer
Neurosurgical Procedures
Pain Measurement
Predictive Value of Tests
Prognosis
Radiation Dosage
Radiosurgery
Risk Factors
Treatment Outcome
Trigeminal Neuralgia
Young Adult