Operative Neurosurgery · 2023 · 12 citations · 34 references
MedicineComputer ScienceSurgeryMachine LearningPain ManagementPain MedicineDecision Support AnalyticsOptimization For Machine LearningPain AssessmentPain OutcomesRepresentation LearningSpinal Cord StimulationCandidate Selection CriteriaMachine Learning AnalyticsMachine Learning Decision SupportMachine Learning For HealthcareNeuropathic Pain ReductionNeuropathic Pain ReliefPain PredictionPatient Outcomes Measurement
Spinal cord stimulation (SCS) is an effective treatment for chronic neuropathic pain. The success of SCS is dependent on candidate selection, response to trialing, and programming optimization. Owing to the subjective nature of these variables, machine learning (ML) offers a powerful tool to augment these processes. Here we explore what work has been done using data analytics and applications of ML in SCS. In addition, we discuss aspects of SCS which have narrowly been influenced by ML and propose the need for further exploration. ML has demonstrated a potential to complement SCS to an extent ranging from assistance with candidate selection to replacing invasive and costly aspects of the surgery. The clinical application of ML in SCS shows promise for improving patient outcomes, reducing costs of treatment, limiting invasiveness, and resulting in a better quality of life for the patient.
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