{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T19:21:54Z","timestamp":1794079314913,"version":"4.8.0"},"reference-count":75,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T00:00:00Z","timestamp":1735776000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T00:00:00Z","timestamp":1735776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100011781","name":"Shriners Hospitals for Children","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100011781","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Commun Med"],"DOI":"10.1038\/s43856-024-00726-1","type":"journal-article","created":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T20:57:02Z","timestamp":1735851422000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["Predicting pediatric patient rehabilitation outcomes after spinal deformity surgery with artificial intelligence"],"prefix":"10.1038","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8972-7342","authenticated-orcid":false,"given":"Wenqi","family":"Shi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8355-3705","authenticated-orcid":false,"given":"Felipe O.","family":"Giuste","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanda","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ben J.","family":"Tamo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0915-6342","authenticated-orcid":false,"given":"Micky C.","family":"Nnamdi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Hornback","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1892-2826","authenticated-orcid":false,"given":"Ashley M.","family":"Carpenter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9070-7680","authenticated-orcid":false,"given":"Coleman","family":"Hilton","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henry J.","family":"Iwinski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J. Michael","family":"Wattenbarger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"May D.","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,2]]},"reference":[{"key":"726_CR1","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1016\/S0140-6736(08)60658-3","volume":"371","author":"SL Weinstein","year":"2008","unstructured":"Weinstein, S. L., Dolan, L. A., Cheng, J. C., Danielsson, A. & Morcuende, J. A. Adolescent idiopathic scoliosis. Lancet 371, 1527\u20131537 (2008).","journal-title":"Lancet"},{"key":"726_CR2","first-page":"1","volume":"1","author":"JC Cheng","year":"2015","unstructured":"Cheng, J. C. et al. Adolescent idiopathic scoliosis. Nat. Rev. Dis. Prim. 1, 1\u201321 (2015).","journal-title":"Nat. Rev. Dis. Prim."},{"key":"726_CR3","unstructured":"White, A. Physical properties and functional biomechanics of the spine. Clin. Biomech. Spine 22 278\u2013283 (1990)."},{"key":"726_CR4","doi-asserted-by":"publisher","first-page":"1293","DOI":"10.1097\/BRS.0000000000003517","volume":"45","author":"M Marrache","year":"2020","unstructured":"Marrache, M., Harris, A. B., Puvanesarajah, V. & Sponseller, P. D. Seasonal variation in the volume of posterior spinal arthrodesis procedures for pediatric scoliosis. Spine 45, 1293\u20131298 (2020).","journal-title":"Spine"},{"key":"726_CR5","doi-asserted-by":"publisher","first-page":"S217","DOI":"10.1097\/01.BRS.0000092461.11181.CD","volume":"28","author":"PO Newton","year":"2003","unstructured":"Newton, P. O. et al. Factors involved in the decision to perform a selective versus nonselective fusion of lenke 1B and 1C (King-Moe II) curves in adolescent idiopathic scoliosis. Spine 28, S217\u2013S223 (2003).","journal-title":"Spine"},{"key":"726_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1748-7161-1-4","volume":"1","author":"S Negrini","year":"2006","unstructured":"Negrini, S. et al. Why do we treat adolescent idiopathic scoliosis? What we want to obtain and to avoid for our patients. sosort 2005 consensus paper. Scoliosis 1, 1\u201314 (2006).","journal-title":"Scoliosis"},{"key":"726_CR7","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1007\/s00247-017-3941-7","volume":"48","author":"AN Alsharief","year":"2018","unstructured":"Alsharief, A. N., El-Hawary, R. & Schmit, P. Pediatric spine imaging post scoliosis surgery. Pediatr. Radiol. 48, 124\u2013140 (2018).","journal-title":"Pediatr. Radiol."},{"key":"726_CR8","doi-asserted-by":"publisher","first-page":"1127","DOI":"10.2106\/JBJS.L.01357","volume":"96","author":"DN Shau","year":"2014","unstructured":"Shau, D. N. et al. Utility of postoperative radiographs for pediatric scoliosis: association between history and physical examination findings and radiographic findings. J. Bone Joint. Surg. Am. 96, 1127\u20131134 (2014).","journal-title":"J. Bone Joint. Surg. Am."},{"key":"726_CR9","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1097\/00007632-200301010-00015","volume":"28","author":"M Asher","year":"2003","unstructured":"Asher, M., Lai, S. M., Burton, D. & Manna, B. The reliability and concurrent validity of the scoliosis research society-22 patient questionnaire for idiopathic scoliosis. Spine 28, 63\u201369 (2003).","journal-title":"Spine"},{"key":"726_CR10","doi-asserted-by":"publisher","first-page":"1795","DOI":"10.1097\/00007632-200007150-00010","volume":"25","author":"LP D\u2019Andrea","year":"2000","unstructured":"D\u2019Andrea, L. P. et al. Do radiographic parameters correlate with clinical outcomes in adolescent idiopathic scoliosis? Spine 25, 1795\u20131802 (2000).","journal-title":"Spine"},{"key":"726_CR11","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1055\/a-1401-0477","volume":"160","author":"K Gem","year":"2022","unstructured":"Gem, K., Hancioglu, S., Bilgi\u00e7, A. & Erkan, S. Comparison of changes in SRS-22 values with improvement in Cobb angles after posterior fusion surgery in adolescent idiopathic scoliosis. Z. Orthop. Unfall. 160, 532\u2013538 (2022).","journal-title":"Z. Orthop. Unfall."},{"key":"726_CR12","first-page":"115","volume":"38","author":"SL Weinstein","year":"1989","unstructured":"Weinstein, S. L. Adolescent idiopathic scoliosis: prevalence and natural history. Instr. Course Lect. 38, 115\u2013128 (1989).","journal-title":"Instr. Course Lect."},{"key":"726_CR13","first-page":"409","volume":"27","author":"LN Pellegrino","year":"2014","unstructured":"Pellegrino, L. N. & Avanzi, O. Prospective evaluation of quality of life in adolescent idiopathic scoliosis before and after surgery. Clin. Spine Surg. 27, 409\u2013414 (2014).","journal-title":"Clin. Spine Surg."},{"key":"726_CR14","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1007\/s00586-012-2547-x","volume":"22","author":"JS Smith","year":"2013","unstructured":"Smith, J. S. et al. Clinical and radiographic parameters that distinguish between the best and worst outcomes of scoliosis surgery for adults. Eur. Spine J. 22, 402\u2013410 (2013).","journal-title":"Eur. Spine J."},{"key":"726_CR15","doi-asserted-by":"publisher","first-page":"349","DOI":"10.3171\/2014.12.SPINE14777","volume":"23","author":"JS Smith","year":"2015","unstructured":"Smith, J. S. et al. Comparison of best versus worst clinical outcomes for adult spinal deformity surgery: a retrospective review of a prospectively collected, multicenter database with 2-year follow-up: presented at the 2015 AANS\/CNS Joint Section on Disorders of the Spine and Peripheral Nerves. J. Neurosurg. Spine 23, 349\u2013359 (2015).","journal-title":"J. Neurosurg. Spine"},{"key":"726_CR16","first-page":"152","volume":"18","author":"TR Kuklo","year":"2005","unstructured":"Kuklo, T. R. et al. Reliability analysis for digital adolescent idiopathic scoliosis measurements. Clin. Spine Surg. 18, 152\u2013159 (2005).","journal-title":"Clin. Spine Surg."},{"key":"726_CR17","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.1097\/01.brs.0000160840.51621.6b","volume":"30","author":"NR Dang","year":"2005","unstructured":"Dang, N. R., Moreau, M. J., Hill, D. L., Mahood, J. K. & Raso, J. Intra-observer reproducibility and interobserver reliability of the radiographic parameters in the spinal deformity study group\u2019s ais radiographic measurement manual. Spine 30, 1064\u20131069 (2005).","journal-title":"Spine"},{"key":"726_CR18","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1007\/s00586-020-06701-3","volume":"30","author":"Y Mihara","year":"2021","unstructured":"Mihara, Y. et al. Predictive factors for correction rate in severe idiopathic scoliosis (Cobb angle\u2265 90\u2218): an analysis of 128 patients. Eur. Spine J. 30, 653\u2013660 (2021).","journal-title":"Eur. Spine J."},{"key":"726_CR19","doi-asserted-by":"publisher","first-page":"49","DOI":"10.4055\/jkoa.1995.30.1.49","volume":"30","author":"SI Suk","year":"1995","unstructured":"Suk, S. I. et al. Segmental pedicle screw fixation in the treatment of thoracic idiopathic scoliosis. J. Korean Orthop. Assoc. 30, 49\u201358 (1995).","journal-title":"J. Korean Orthop. Assoc."},{"key":"726_CR20","doi-asserted-by":"publisher","first-page":"E1402","DOI":"10.1097\/BRS.0b013e31822815ff","volume":"36","author":"JO Sanders","year":"2011","unstructured":"Sanders, J. O. et al. Fixation points within the main thoracic curve: does more instrumentation produce greater curve correction and improved results? Spine 36, E1402\u2013E1406 (2011).","journal-title":"Spine"},{"key":"726_CR21","doi-asserted-by":"publisher","first-page":"845","DOI":"10.1097\/BRS.0b013e31819e2753","volume":"34","author":"BS Lonner","year":"2009","unstructured":"Lonner, B. S. et al. Treatment of thoracic scoliosis: are monoaxial thoracic pedicle screws the best form of fixation for correction? Spine 34, 845\u2013851 (2009).","journal-title":"Spine"},{"key":"726_CR22","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.1007\/s00586-021-06786-4","volume":"30","author":"D Cawley","year":"2021","unstructured":"Cawley, D. et al. The impact of corrective surgery on health-related quality of life subclasses in adult scoliosis: will degree of correction prognosticate degree of improvement? Eur. Spine J. 30, 2033\u20132039 (2021).","journal-title":"Eur. Spine J."},{"key":"726_CR23","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1097\/BSD.0000000000000822","volume":"33","author":"B Aghdasi","year":"2020","unstructured":"Aghdasi, B. et al. Patient-reported outcomes following surgical intervention for adolescent idiopathic scoliosis: a systematic review and meta-analysis. Clin. Spine Surg. 33, 24\u201334 (2020).","journal-title":"Clin. Spine Surg."},{"key":"726_CR24","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1097\/BRS.0000000000000961","volume":"40","author":"JL Gum","year":"2015","unstructured":"Gum, J. L. et al. Srs22r appearance domain correlates most with patient satisfaction after adult deformity surgery to the sacrum at 5-year follow-up. Spine 40, 1297\u20131302 (2015).","journal-title":"Spine"},{"key":"726_CR25","doi-asserted-by":"publisher","first-page":"E45","DOI":"10.1097\/BRS.0000000000002753","volume":"44","author":"J Yang","year":"2019","unstructured":"Yang, J. et al. Determinants of patient satisfaction 2 years after spinal deformity surgery: a latent class analysis. Spine 44, E45\u2013E52 (2019).","journal-title":"Spine"},{"key":"726_CR26","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1097\/BRS.0000000000000761","volume":"40","author":"CH Crawford III","year":"2015","unstructured":"Crawford III, C. H., Glassman, S. D., Bridwell, K. H., Berven, S. H. & Carreon, L. Y. The minimum clinically important difference in SRS-22r total score, appearance, activity and pain domains after surgical treatment of adult spinal deformity. Spine 40, 377\u2013381 (2015).","journal-title":"Spine"},{"key":"726_CR27","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1016\/j.spinee.2007.01.008","volume":"7","author":"AG Copay","year":"2007","unstructured":"Copay, A. G., Subach, B. R., Glassman, S. D., Polly Jr, D. W. & Schuler, T. C. Understanding the minimum clinically important difference: a review of concepts and methods. Spine J. 7, 541\u2013546 (2007).","journal-title":"Spine J."},{"key":"726_CR28","doi-asserted-by":"publisher","first-page":"2079","DOI":"10.1097\/BRS.0b013e3181c61fd7","volume":"35","author":"LY Carreon","year":"2010","unstructured":"Carreon, L. Y. et al. The minimum clinically important difference in scoliosis research society-22 appearance, activity, and pain domains after surgical correction of adolescent idiopathic scoliosis. Spine 35, 2079\u20132083 (2010).","journal-title":"Spine"},{"key":"726_CR29","doi-asserted-by":"publisher","first-page":"E847","DOI":"10.1097\/BRS.0000000000003434","volume":"45","author":"T Fujishiro","year":"2020","unstructured":"Fujishiro, T. et al. Clinical performance and concurrent validity of the adult spinal deformity surgical decision-making score. Spine 45, E847\u2013E855 (2020).","journal-title":"Spine"},{"key":"726_CR30","doi-asserted-by":"publisher","first-page":"847","DOI":"10.1093\/neuros\/nyx303","volume":"82","author":"BJ Neuman","year":"2018","unstructured":"Neuman, B. J. et al. Development and validation of a novel adult spinal deformity surgical invasiveness score: analysis of 464 patients. Neurosurgery 82, 847\u2013853 (2018).","journal-title":"Neurosurgery"},{"key":"726_CR31","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1016\/j.spinee.2017.06.042","volume":"18","author":"F Pellis\u00e9","year":"2018","unstructured":"Pellis\u00e9, F. et al. The Adult Deformity Surgery Complexity Index (ADSCI): a valid tool to quantify the complexity of posterior adult spinal deformity surgery and predict postoperative complications. Spine J. 18, 216\u2013225 (2018).","journal-title":"Spine J."},{"key":"726_CR32","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1093\/pch\/12.9.771","volume":"12","author":"JA Janicki","year":"2007","unstructured":"Janicki, J. A. & Alman, B. Scoliosis: Review of diagnosis and treatment. Paediatr. Child Health 12, 771\u2013776 (2007).","journal-title":"Paediatr. Child Health"},{"key":"726_CR33","doi-asserted-by":"publisher","first-page":"S101","DOI":"10.1097\/BRS.0b013e318134ed0e","volume":"32","author":"AJ Danielsson","year":"2007","unstructured":"Danielsson, A. J. What impact does spinal deformity correction for adolescent idiopathic scoliosis make on quality of life? Spine 32, S101\u2013S108 (2007).","journal-title":"Spine"},{"key":"726_CR34","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1001\/jama.289.5.559","volume":"289","author":"SL Weinstein","year":"2003","unstructured":"Weinstein, S. L. et al. Health and function of patients with untreated idiopathic scoliosis: a 50-year natural history study. JAMA 289, 559\u2013567 (2003).","journal-title":"JAMA"},{"key":"726_CR35","doi-asserted-by":"publisher","first-page":"1998","DOI":"10.1007\/s00586-019-06079-x","volume":"28","author":"CP Ames","year":"2019","unstructured":"Ames, C. P. et al. Development of predictive models for all individual questions of srs-22r after adult spinal deformity surgery: a step toward individualized medicine. Eur. Spine J. 28, 1998\u20132011 (2019).","journal-title":"Eur. Spine J."},{"key":"726_CR36","doi-asserted-by":"publisher","first-page":"3051","DOI":"10.1007\/s00586-020-06611-4","volume":"29","author":"K Hayashi","year":"2020","unstructured":"Hayashi, K. et al. Prediction of satisfaction after correction surgery for adult spinal deformity: differences between younger and older patients. Eur. Spine J. 29, 3051\u20133062 (2020).","journal-title":"Eur. Spine J."},{"key":"726_CR37","doi-asserted-by":"publisher","first-page":"634","DOI":"10.1001\/jamasurg.2018.0072","volume":"153","author":"S Khor","year":"2018","unstructured":"Khor, S. et al. Development and validation of a prediction model for pain and functional outcomes after lumbar spine surgery. JAMA Surg. 153, 634\u2013642 (2018).","journal-title":"JAMA Surg."},{"key":"726_CR38","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1007\/s00586-019-06189-6","volume":"29","author":"A Quddusi","year":"2020","unstructured":"Quddusi, A. et al. External validation of a prediction model for pain and functional outcome after elective lumbar spinal fusion. Eur. Spine J. 29, 374\u2013383 (2020).","journal-title":"Eur. Spine J."},{"key":"726_CR39","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/s00586-019-06200-0","volume":"29","author":"K Hayashi","year":"2020","unstructured":"Hayashi, K. et al. Mental health status and sagittal spinopelvic alignment correlate with self-image in patients with adult spinal deformity before and after corrective surgery. Eur. Spine J. 29, 63\u201372 (2020).","journal-title":"Eur. Spine J."},{"key":"726_CR40","doi-asserted-by":"publisher","first-page":"915","DOI":"10.1097\/BRS.0000000000002974","volume":"44","author":"CP Ames","year":"2019","unstructured":"Ames, C. P. et al. 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. Spine 44, 915\u2013926 (2019).","journal-title":"Spine"},{"key":"726_CR41","doi-asserted-by":"publisher","first-page":"1144","DOI":"10.1097\/BRS.0000000000003031","volume":"44","author":"CP Ames","year":"2019","unstructured":"Ames, C. P. et al. Development of deployable predictive models for minimal clinically important difference achievement across the commonly used health-related quality of life instruments in adult spinal deformity surgery. Spine 44, 1144\u20131153 (2019).","journal-title":"Spine"},{"key":"726_CR42","doi-asserted-by":"publisher","first-page":"E5","DOI":"10.3171\/2019.2.FOCUS18723","volume":"46","author":"A Siccoli","year":"2019","unstructured":"Siccoli, A., Marlies, P., Schr\u00f6der, M. L. & Staartjes, V. E. Machine learning\u2013based preoperative predictive analytics for lumbar spinal stenosis. Neurosurg. Focus 46, E5 (2019).","journal-title":"Neurosurg. Focus"},{"key":"726_CR43","doi-asserted-by":"publisher","first-page":"1377","DOI":"10.3390\/jpm11121377","volume":"11","author":"P Berjano","year":"2021","unstructured":"Berjano, P. et al. The influence of baseline clinical status and surgical strategy on early good to excellent result in spinal lumbar arthrodesis: a machine learning approach. J. Pers. Med. 11, 1377 (2021).","journal-title":"J. Pers. Med."},{"key":"726_CR44","doi-asserted-by":"publisher","first-page":"E2","DOI":"10.3171\/2017.9.FOCUS17494","volume":"43","author":"T Oh","year":"2017","unstructured":"Oh, T. et al. Potential of predictive computer models for preoperative patient selection to enhance overall quality-adjusted life years gained at 2-year follow-up: a simulation in 234 patients with adult spinal deformity. Neurosurg. Focus 43, E2 (2017).","journal-title":"Neurosurg. Focus"},{"key":"726_CR45","doi-asserted-by":"publisher","first-page":"559387","DOI":"10.3389\/fbioe.2020.559387","volume":"8","author":"L Peng","year":"2020","unstructured":"Peng, L. et al. Prediction of proximal junctional kyphosis after posterior scoliosis surgery with machine learning in the lenke 5 adolescent idiopathic scoliosis patient. Front. Bioeng. Biotechnol. 8, 559387 (2020).","journal-title":"Front. Bioeng. Biotechnol."},{"key":"726_CR46","doi-asserted-by":"publisher","first-page":"e0273002","DOI":"10.1371\/journal.pone.0273002","volume":"17","author":"A Alfraihat","year":"2022","unstructured":"Alfraihat, A., Samdani, A. F. & Balasubramanian, S. Predicting curve progression for adolescent idiopathic scoliosis using random forest model. PLoS ONE 17, e0273002 (2022).","journal-title":"PLoS ONE"},{"key":"726_CR47","doi-asserted-by":"publisher","first-page":"736","DOI":"10.3171\/2016.10.SPINE16197","volume":"26","author":"JK Scheer","year":"2017","unstructured":"Scheer, J. K. et al. Development of a preoperative predictive model for major complications following adult spinal deformity surgery. J. Neurosurg. Spine 26, 736\u2013743 (2017).","journal-title":"J. Neurosurg. Spine"},{"key":"726_CR48","doi-asserted-by":"publisher","first-page":"e422","DOI":"10.1016\/j.wneu.2018.04.064","volume":"115","author":"MM Safaee","year":"2018","unstructured":"Safaee, M. M. et al. Predictive modeling of length of hospital stay following adult spinal deformity correction: analysis of 653 patients with an accuracy of 75% within 2 days. World Neurosurg. 115, e422\u2013e427 (2018).","journal-title":"World Neurosurg."},{"key":"726_CR49","doi-asserted-by":"publisher","first-page":"E252","DOI":"10.1097\/BRS.0000000000003242","volume":"45","author":"CP Ames","year":"2020","unstructured":"Ames, C. P. et al. Utilization of predictive modeling to determine episode of care costs and to accurately identify catastrophic cost nonwarranty outlier patients in adult spinal deformity surgery: a step toward bundled payments and risk sharing. Spine 45, E252\u2013E265 (2020).","journal-title":"Spine"},{"key":"726_CR50","doi-asserted-by":"publisher","first-page":"E6","DOI":"10.3171\/2018.8.FOCUS18340","volume":"45","author":"AV Karhade","year":"2018","unstructured":"Karhade, A. V. et al. Development of machine learning algorithms for prediction of discharge disposition after elective inpatient surgery for lumbar degenerative disc disorders. Neurosurg. Focus 45, E6 (2018).","journal-title":"Neurosurg. Focus"},{"key":"726_CR51","doi-asserted-by":"publisher","first-page":"E11","DOI":"10.3171\/2018.8.FOCUS18246","volume":"45","author":"JK Scheer","year":"2018","unstructured":"Scheer, J. K. et al. Development of a validated computer-based preoperative predictive model for pseudarthrosis with 91% accuracy in 336 adult spinal deformity patients. Neurosurg. Focus 45, E11 (2018).","journal-title":"Neurosurg. Focus"},{"key":"726_CR52","doi-asserted-by":"publisher","first-page":"E1328","DOI":"10.1097\/BRS.0000000000001598","volume":"41","author":"JK Scheer","year":"2016","unstructured":"Scheer, J. K. et al. Development of validated computer-based preoperative predictive model for proximal junction failure (PJF) or clinically significant PJK with 86% accuracy based on 510 ASD patients with 2-year follow-up. Spine 41, E1328\u2013E1335 (2016).","journal-title":"Spine"},{"key":"726_CR53","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1016\/j.spinee.2018.11.009","volume":"19","author":"VE Staartjes","year":"2019","unstructured":"Staartjes, V. E., Marlies, P., Vandertop, W. P. & Schr\u00f6der, M. L. Deep learning-based preoperative predictive analytics for patient-reported outcomes following lumbar discectomy: feasibility of center-specific modeling. Spine J. 19, 853\u2013861 (2019).","journal-title":"Spine J."},{"key":"726_CR54","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1097\/BRS.0000000000002442","volume":"43","author":"JS Kim","year":"2018","unstructured":"Kim, J. S. et al. Examining the ability of artificial neural networks machine learning models to accurately predict complications following posterior lumbar spine fusion. Spine 43, 853 (2018).","journal-title":"Spine"},{"key":"726_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-022-00689-4","volume":"5","author":"LR Soenksen","year":"2022","unstructured":"Soenksen, L. R. et al. Integrated multimodal artificial intelligence framework for healthcare applications. NPJ Digit. Med. 5, 1\u201310 (2022).","journal-title":"NPJ Digit. Med."},{"key":"726_CR56","doi-asserted-by":"crossref","unstructured":"Giuste, F. et al. Explainable artificial intelligence methods in combating pandemics: a systematic review. In: IEEE Reviews in Biomedical Engineering (IEEE, 2022).","DOI":"10.1109\/RBME.2022.3185953"},{"key":"726_CR57","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12911-018-0731-6","volume":"19","author":"M Huber","year":"2019","unstructured":"Huber, M., Kurz, C. & Leidl, R. Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning. BMC Med. Inform. Decis. Mak. 19, 1\u201313 (2019).","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"726_CR58","unstructured":"Lundberg, S. M. & Lee, S.-I. A unified approach to interpreting model predictions. (ed. Guyon, I. et al.) In: Advances in Neural Information Processing Systems 30, 4765\u20134774 (Curran Associates, Inc., 2017). http:\/\/papers.nips.cc\/paper\/7062-a-unified-approach-to-interpreting-model-predictions.pdf."},{"key":"726_CR59","doi-asserted-by":"publisher","first-page":"2522","DOI":"10.1038\/s42256-019-0138-9","volume":"2","author":"SM Lundberg","year":"2020","unstructured":"Lundberg, S. M. et al. From local explanations to global understanding with explainable AI for trees. Nat. Mach. Intell. 2, 2522\u20135839 (2020).","journal-title":"Nat. Mach. Intell."},{"key":"726_CR60","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1038\/s41551-018-0304-0","volume":"2","author":"SM Lundberg","year":"2018","unstructured":"Lundberg, S. M. et al. Explainable machine-learning predictions for the prevention of hypoxaemia during surgery. Nat. Biomed. Eng. 2, 749 (2018).","journal-title":"Nat. Biomed. Eng."},{"key":"726_CR61","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","volume":"58","author":"AB Arrieta","year":"2020","unstructured":"Arrieta, A. B. et al. Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion 58, 82\u2013115 (2020).","journal-title":"Inf. Fusion"},{"key":"726_CR62","unstructured":"Guo, C., Pleiss, G., Sun, Y. & Weinberger, K. Q. On calibration of modern neural networks. In: International Conference on Machine Learning, 1321\u20131330 (PMLR, 2017)."},{"key":"726_CR63","unstructured":"M\u00fcller, R., Kornblith, S. & Hinton, G. E. When does label smoothing help? Adv. Neural Inf. Process. Syst. 32, 1\u201310 (2019)."},{"key":"726_CR64","doi-asserted-by":"crossref","unstructured":"Thulasidasan, S., Chennupati, G., Bilmes, J. A., Bhattacharya, T. & Michalak, S. On mixup training: Improved calibration and predictive uncertainty for deep neural networks. Adv. Neural Inf. Process. Syst. 32, 1\u201312 (2019).","DOI":"10.2172\/1525811"},{"key":"726_CR65","unstructured":"Gal, Y. & Ghahramani, Z. Dropout as a Bayesian approximation: representing model uncertainty in deep learning. In International Conference on Machine Learning, 1050\u20131059 (PMLR, 2016)."},{"key":"726_CR66","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-022-11012-2","volume":"12","author":"C Meng","year":"2022","unstructured":"Meng, C., Trinh, L., Xu, N., Enouen, J. & Liu, Y. Interpretability and fairness evaluation of deep learning models on mimic-iv dataset. Sci. Rep. 12, 1\u201328 (2022).","journal-title":"Sci. Rep."},{"key":"726_CR67","doi-asserted-by":"crossref","unstructured":"Brunton, S. L. & Kutz, J. N. Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control (Cambridge University Press, 2022).","DOI":"10.1017\/9781009089517"},{"key":"726_CR68","unstructured":"Nixon, J. et al. Measuring calibration in deep learning. https:\/\/arxiv.org\/abs\/1904.01685 (2020)."},{"key":"726_CR69","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1016\/j.wneu.2017.03.003","volume":"102","author":"A Jain","year":"2017","unstructured":"Jain, A. et al. Early patient-reported outcomes predict 3-year outcomes in operatively treated patients with adult spinal deformity. World Neurosurg. 102, 258\u2013262 (2017).","journal-title":"World Neurosurg."},{"key":"726_CR70","doi-asserted-by":"publisher","first-page":"2312","DOI":"10.1007\/s00586-018-5572-6","volume":"27","author":"T Fujishiro","year":"2018","unstructured":"Fujishiro, T. et al. Decision-making factors in the treatment of adult spinal deformity. Eur. Spine J. 27, 2312\u20132321 (2018).","journal-title":"Eur. Spine J."},{"key":"726_CR71","doi-asserted-by":"crossref","unstructured":"Lawless, M. H. et al. Radiographic and patient-reported outcomes of lordotic versus non-lordotic static interbody devices in minimally invasive transforaminal lumbar interbody fusion: a longitudinal comparative cohort study. Cureus 14, 1\u201310 (2022).","DOI":"10.7759\/cureus.21273"},{"key":"726_CR72","doi-asserted-by":"crossref","unstructured":"Shi, W. et al. A FHIR-compliant application for multi-site and multi-modality pediatric scoliosis patient rehabilitation. In 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1524\u20131527 (IEEE, 2021).","DOI":"10.1109\/BIBM52615.2021.9669649"},{"key":"726_CR73","doi-asserted-by":"crossref","unstructured":"Hornback, A. et al. Development of a generalizable multi-site and multi-modality clinical data cloud infrastructure for pediatric patient care. In Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, 1\u201310 (2022).","DOI":"10.1145\/3535508.3545565"},{"key":"726_CR74","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-022-00641-6","volume":"5","author":"K Lam","year":"2022","unstructured":"Lam, K. et al. A Delphi consensus statement for digital surgery. NPJ Digit. Med. 5, 1\u20139 (2022).","journal-title":"NPJ Digit. Med."},{"key":"726_CR75","unstructured":"Shi, W. GL-SMART: https:\/\/github.com\/wshi83\/GL-SMART (2024)."}],"container-title":["Communications Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s43856-024-00726-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s43856-024-00726-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s43856-024-00726-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T21:05:09Z","timestamp":1735851909000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s43856-024-00726-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,2]]},"references-count":75,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["726"],"URL":"https:\/\/doi.org\/10.1038\/s43856-024-00726-1","relation":{},"ISSN":["2730-664X"],"issn-type":[{"value":"2730-664X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,2]]},"assertion":[{"value":"25 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1"}}