| Literature DB >> 34862557 |
Elie Massaad1, Yoon Ha2, Ganesh M Shankar1, John H Shin3.
Abstract
Artificial intelligence is poised to influence various aspects of patient care, and neurosurgery is one of the most uprising fields where machine learning is being applied to provide surgeons with greater insight about the pathophysiology and prognosis of neurological conditions. This chapter provides a guide for clinicians on relevant aspects of machine learning and reviews selected application of these methods in intramedullary spinal cord tumors. The potential areas of application of machine learning extend far beyond the analyses of clinical data to include several areas of artificial intelligence, such as genomics and computer vision. Integration of various sources of data and application of advanced analytical approaches could improve risk assessment for intramedullary tumors.Entities:
Keywords: Artificial intelligence; Intramedullary tumors; Machine learning; Prediction; Spine surgery
Mesh:
Year: 2022 PMID: 34862557 DOI: 10.1007/978-3-030-85292-4_37
Source DB: PubMed Journal: Acta Neurochir Suppl ISSN: 0065-1419