000041648 001__ 41648
000041648 005__ 20240125142325.0
000041648 0247_ $$2doi$$a10.6083/bpxhc41648
000041648 037__ $$aIR
000041648 041__ $$aeng
000041648 245__ $$aA machine learning model utilizing only six  variables can accurately predict outcomes  following posterior cervical fusion
000041648 260__ $$bOregon Health and Science University
000041648 269__ $$a2023-08-25
000041648 336__ $$aAbstract
000041648 520__ $$aThe practical application of machine learning models in clinical medicine is limited by the substantial amount of time required to input the many variables that the models depend on. This study aimed to develop a good-performing prediction tool for outcomes after posterior cervical fusion procedures using a limited number of pre-operative variables.
000041648 540__ $$fCC BY
000041648 542__ $$fIn copyright - joint owners
000041648 650__ $$aBody Mass Index$$028801
000041648 650__ $$aSpinal Fusion$$026286
000041648 650__ $$aSpinal Diseases$$026285
000041648 650__ $$aMachine Learning$$011449
000041648 650__ $$aAnkylosis$$014795
000041648 650__ $$aAlbumins$$014394
000041648 650__ $$aHumans$$020376
000041648 650__ $$aArtificial Intelligence$$015109
000041648 6531_ $$acervical fusion
000041648 6531_ $$aposterior cervical fusion
000041648 6531_ $$aspinal deformity
000041648 691__ $$aSchool of Medicine$$041369
000041648 692__ $$aDepartment of Orthopaedics and Rehabilitation$$041436
000041648 7001_ $$aSmith, Spencer$$uOregon Health and Science University$$041354
000041648 7001_ $$aYoo, Jung$$uOregon Health and Science University$$041354
000041648 711__ $$aResearch Week$$uOregon Health and Science University$$d2023
000041648 8564_ $$994d51b8e-698f-4fd4-a825-6757547052d7$$s275344$$uhttps://digitalcollections.ohsu.edu/record/41648/files/ResearchWeek.2023.Smith.Spencer.pdf
000041648 980__ $$aResearch Week
000041648 981__ $$aPublished$$b2023-08-25