Artificial Intelligence Based Hierarchical Clustering of Patient Types and Intervention Categories in Adult Spinal Deformity Surgery Towards a New Classification Scheme that Predicts Quality and Value

Ames, Christopher P.; Smith, Justin S.; Pellise, Ferran; Kelly, Michael; Alanay, Ahmet; Acaroglu, Emre; Sanchez Perez\\-Grueso, Francisco Javier; Kleinstuck, Frank; Obeid, Ibrahim; Vila\\-Casademunt, Alba; Shaffrey, Jr., Christopher I.; Burton, Douglas; Lafage, Virginie; Schwab, Frank; Shaffrey Sr, Christopher I. Sr; Bess, Shay; Serra\\-Burriel, Miguel; European Spine Study Grp; Int Spine Study Grp

doi:10.1097/BRS.0000000000002974

Artificial Intelligence Based Hierarchical Clustering of Patient Types and Intervention Categories in Adult Spinal Deformity Surgery Towards a New Classification Scheme that Predicts Quality and Value

Date

2019

Authors

Sanchez Perez\\-Grueso, Francisco Javier

Kleinstuck, Frank

Obeid, Ibrahim

Vila\\-Casademunt, Alba

dc.identifier.doi

10.1097/BRS.0000000000002974

dc.identifier.other

WOS:000480754900010

Publisher

LIPPINCOTT WILLIAMS \& WILKINS

DOI

10.1097/BRS.0000000000002974

Keywords

adult spinal deformity , artificial intelligence , classification , complications , hierarchical clustering , outcomes , predictive analytics , quality , scoliosis , surgery

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https://openaccess.acibadem.edu.tr/handle/11443/7983

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WOS

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Artificial Intelligence Based Hierarchical Clustering of Patient Types and Intervention Categories in Adult Spinal Deformity Surgery Towards a New Classification Scheme that Predicts Quality and Value

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