Neurosurgery
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Multicenter Study
Methods and Impact for Using Federated Learning to Collaborate on Clinical Research.
The development of accurate machine learning algorithms requires sufficient quantities of diverse data. This poses a challenge in health care because of the sensitive and siloed nature of biomedical information. Decentralized algorithms through federated learning (FL) avoid data aggregation by instead distributing algorithms to the data before centrally updating one global model. ⋯ This study demonstrates the feasibility of implementing a federated network for multi-institutional collaboration among clinicians and using FL to conduct machine learning research, thereby opening a new paradigm for neurosurgical collaboration.
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Multicenter Study
Neurosurgical Outcomes for Pediatric Central Nervous System Tumors in the United States.
Limited data exist on pediatric central nervous system (CNS) tumors, and the results from the National Cancer Database, the largest multicenter national cancer registry, have not previously been comprehensively reported. ⋯ There is substantial variability in surgical morbidity and mortality of pediatric CNS tumors. Additional investigation is warranted to reduce outcome differences that may be based on socioeconomic factors.