Article
Machine learning clustering of adult spinal deformity patients identifies four prognostic phenotypes: a multicenter prospective cohort analysis with single surgeon external validation.
The spine journal : official journal of the North American Spine Society - 1 Jun 2024
Mohanty Sarthak, Hassan Fthimnir M, Lenke Lawrence G, Lewerenz Erik, Passias Peter G, Klineberg Eric O, Lafage Virginie, Smith Justin S, Hamilton D Kojo, Gum Jeffrey L, Lafage Renaud, Mullin Jeffrey, Diebo Bassel, Buell Thomas J, Kim Han Jo, Kebaish Khalid, Eastlack Robert, Daniels Alan H, Mundis Gregory, Hostin Richard, Protopsaltis Themistocles S, Hart Robert A, Gupta Munish, Schwab Frank J, Shaffrey Christopher I, Ames Christopher P, Burton Douglas, Bess Shay
Abstract excerpt
BACKGROUND CONTEXT: Among adult spinal deformity (ASD) patients, heterogeneity in patient pathology, surgical expectations, baseline impairments, and frailty complicates comparisons in clinical outcomes and research. This study aims to qualitatively segment ASD patients using machine learning-based clustering on a large, multicenter, prospectively gathered ASD cohort. PURPOSE: To qualitatively segment adult...
Read the complete abstract on PubMedTopics
Share this publication in a Topic to start or enrich a Post.