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Artificial intelligence (AI) is a set of theories and techniques for studying artificial intelligence, which realizes machine intelligence by simulating and expanding human intelligence. With the continuous development of the multidisciplinary integration trend of modern medicine, artificial intelligence is used more and more in the diagnosis and treatment of scoliosis. Artificial intelligence has been widely used in the study of scoliosis and has penetrated into all fields of clinical practice of scoliosis. At present, artificial intelligence has shown good application prospects in early screening, diagnosis, treatment decision making, intraoperative operation, and prognosis prediction of scoliosis. This paper mainly summarizes the application of artificial intelligence in the clinical practice of scoliosis, and briefly introduces the AI model and its specific applications. In addition, this paper also discusses the limitations and future development of artificial intelligence. In the future, artificial intelligence will bring greater convenience to the diagnosis and treatment of scoliosis and provide better therapeutic effects for patients.<\/jats:p>","DOI":"10.3390\/jcm12237382","type":"journal-article","created":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T03:53:52Z","timestamp":1701230032000},"page":"7382","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Artificial Intelligence in Scoliosis: Current Applications and Future Directions"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0152-2439","authenticated-orcid":false,"given":"Haozhi","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Orthopaedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changfa","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daoyun","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kuan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Orthopedics, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Orthopedic Surgery, Beijing Jishuitan Hospital, Fourth Clinical College of Peking University, Jishuitan Orthopaedic College of Tsinghua University, Beijing 100035, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Orthopedic Surgery, Beijing Jishuitan Hospital, Fourth Clinical College of Peking University, Jishuitan Orthopaedic College of Tsinghua University, Beijing 100035, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Orthopaedics, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,29]]},"reference":[{"key":"ref_1","first-page":"193","article-title":"Adolescent idiopathic scoliosis: Diagnosis and management","volume":"89","author":"Horne","year":"2014","journal-title":"Am. Fam. Physician"},{"key":"ref_2","first-page":"55","article-title":"Scoliosis: An Overview","volume":"93","author":"Mesiti","year":"2021","journal-title":"Radiol. Technol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s13013-017-0145-8","article-title":"2016 SOSORT guidelines: Orthopaedic and rehabilitation treatment of idiopathic scoliosis during growth","volume":"13","author":"Negrini","year":"2018","journal-title":"Scoliosis Spinal Disord."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"111","DOI":"10.3233\/BMR-130438","article-title":"Scoliosis: Review of types of curves, etiological theories and conservative treatment","volume":"27","author":"Shakil","year":"2014","journal-title":"J. Back Musculoskelet. Rehabil."},{"key":"ref_5","first-page":"821","article-title":"Lenke and King classification systems for adolescent idiopathic scoliosis: Interobserver agreement and postoperative results","volume":"4","author":"Soleimanpour","year":"2011","journal-title":"Int. J. Gen. Med."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.2106\/00004623-200108000-00006","article-title":"Adolescent idiopathic scoliosis: A new classification to determine extent of spinal arthrodesis","volume":"83","author":"Lenke","year":"2001","journal-title":"J. Bone Jt. Surg. Am."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1518","DOI":"10.1016\/j.spinee.2019.03.008","article-title":"Modified PUMC classification for adolescent idiopathic scoliosis","volume":"19","author":"Zhuang","year":"2019","journal-title":"Spine J."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1097\/CM9.0000000000000652","article-title":"Research progress on the etiology and pathogenesis of adolescent idiopathic scoliosis","volume":"133","author":"Peng","year":"2020","journal-title":"Chin. Med. J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"702","DOI":"10.2106\/00004623-198163050-00003","article-title":"Idiopathic scoliosis: Long-term follow-up and prognosis in untreated patients","volume":"63","author":"Weinstein","year":"1981","journal-title":"J. Bone Jt. Surg. Am."},{"key":"ref_10","first-page":"19","article-title":"Adolescent Idiopathic Scoliosis: Common Questions and Answers","volume":"101","author":"Kuznia","year":"2020","journal-title":"Am. Fam. Physician"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1038\/s41551-018-0305-z","article-title":"Artificial intelligence in healthcare","volume":"2","author":"Yu","year":"2018","journal-title":"Nat. Biomed. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"637","DOI":"10.14245\/ns.1938410.205","article-title":"Artificial Intelligence and the Future of Spine Surgery","volume":"16","author":"Joshi","year":"2019","journal-title":"Neurospine"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"l6927","DOI":"10.1136\/bmj.l6927","article-title":"Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness","volume":"368","author":"Vollmer","year":"2020","journal-title":"BMJ"},{"key":"ref_14","first-page":"14","article-title":"Introduction to Machine Learning, Neural Networks, and Deep Learning","volume":"9","author":"Choi","year":"2020","journal-title":"Transl. Vis. Sci. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"67","DOI":"10.21037\/atm-20-5495","article-title":"A narrative review of machine learning as promising revolution in clinical practice of scoliosis","volume":"9","author":"Chen","year":"2021","journal-title":"Ann. Transl. Med."},{"key":"ref_16","first-page":"9","article-title":"Robotic-Assisted Spine Surgery: History, Efficacy, Cost, And Future Trends","volume":"6","author":"Gendreau","year":"2019","journal-title":"Robot Surg."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1001\/jama.2017.11669","article-title":"Screening for Adolescent Idiopathic Scoliosis: Evidence Report and Systematic Review for the US Preventive Services Task Force","volume":"319","author":"Dunn","year":"2018","journal-title":"JAMA"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1080\/10255840008915265","article-title":"Use of Neural Networks to Correlate Spine and Rib Deformity in Scoliosis","volume":"3","author":"Jaremko","year":"2000","journal-title":"Comput. Methods Biomech. Biomed. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1109\/TITB.2005.855526","article-title":"A support vector machines classifier to assess the severity of idiopathic scoliosis from surface topography","volume":"10","author":"Ramirez","year":"2006","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Yang, J., Zhang, K., Fan, H., Huang, Z., Xiang, Y., Yang, J., He, L., Zhang, L., Yang, Y., and Li, R. (2019). Development and validation of deep learning algorithms for scoliosis screening using back images. Commun. Biol., 2.","DOI":"10.1038\/s42003-019-0635-8"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"697","DOI":"10.14245\/ns.1938426.213","article-title":"An Application of Artificial Intelligence to Diagnostic Imaging of Spine Disease: Estimating Spinal Alignment From Moir\u00e9 Images","volume":"16","author":"Watanabe","year":"2019","journal-title":"Neurospine"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Greer, H., Gerber, S., Niethammer, M., Kwitt, R., McCormick, M., Chittajallu, D., Siekierski, N., Oetgen, M., Cleary, K., and Aylward, S. (2018, January 4\u20137). Scoliosis Screening and Monitoring Using Self Contained Ultrasound and Neural Networks. Proceedings of the 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Washington, DC, USA.","DOI":"10.1109\/ISBI.2018.8363857"},{"key":"ref_23","unstructured":"Wei, J., Tay, Y., Bommasani, R., Raffel, C., Zoph, B., Borgeaud, S., Yogatama, D., Bosma, M., Zhou, D., and Metzler, D. (2022). Emergent abilities of large language models. arXiv."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1930","DOI":"10.1038\/s41591-023-02448-8","article-title":"Large language models in medicine","volume":"29","author":"Thirunavukarasu","year":"2023","journal-title":"Nat. Med."},{"key":"ref_25","unstructured":"Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., and Clark, J. (2021, January 18\u201324). Learning transferable visual models from natural language supervision. Proceedings of the International conference on machine learning, in virtual."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Fabijan, A., Fabijan, R., Zawadzka-Fabijan, A., Nowos\u0142awska, E., Zakrzewski, K., and Polis, B. (2023). Evaluating Scoliosis Severity Based on Posturographic X-ray Images Using a Contrastive Language-Image Pretraining Model. Diagnostics, 13.","DOI":"10.3390\/diagnostics13132142"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"E780","DOI":"10.1097\/BRS.0b013e3181f0825a","article-title":"Reliability and accuracy analysis of a new semiautomatic radiographic measurement software in adult scoliosis","volume":"36","author":"Aubin","year":"2011","journal-title":"Spine"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Jin, C., Wang, S., Yang, G., Li, E., and Liang, Z. (2022). A Review of the Methods on Cobb Angle Measurements for Spinal Curvature. Sensors, 22.","DOI":"10.3390\/s22093258"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1007\/BF00223081","article-title":"Variation in Cobb angle measurements in scoliosis","volume":"23","author":"Pruijs","year":"1994","journal-title":"Skelet. Radiol."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Weng, C.H., Wang, C.L., Huang, Y.J., Yeh, Y.C., Fu, C.J., Yeh, C.Y., and Tsai, T.T. (2019). Artificial Intelligence for Automatic Measurement of Sagittal Vertical Axis Using ResUNet Framework. J. Clin. Med., 8.","DOI":"10.3390\/jcm8111826"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"115145","DOI":"10.1109\/ACCESS.2021.3081697","article-title":"BoostNet: A Boosted Convolutional Neural Network for Image Blind Denoising","volume":"9","author":"Vo","year":"2021","journal-title":"IEEE Access"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.media.2018.05.005","article-title":"Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net","volume":"48","author":"Wu","year":"2018","journal-title":"Med. Image Anal."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"101542","DOI":"10.1016\/j.media.2019.101542","article-title":"Accurate automated Cobb angles estimation using multi-view extrapolation net","volume":"58","author":"Wang","year":"2019","journal-title":"Med. Image Anal."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"102277","DOI":"10.1016\/j.media.2021.102277","article-title":"MPF-net: An effective framework for automated cobb angle estimation","volume":"75","author":"Zhang","year":"2022","journal-title":"Med. Image Anal."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s11517-009-0556-7","article-title":"Computer-aided assessment of scoliosis on posteroanterior radiographs","volume":"48","author":"Zhang","year":"2010","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1007\/s10278-008-9127-y","article-title":"Automatic Cobb measurement of scoliosis based on fuzzy Hough Transform with vertebral shape prior","volume":"22","author":"Zhang","year":"2009","journal-title":"J. Digit. Imaging"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1943","DOI":"10.1007\/s10916-011-9654-9","article-title":"Automatic quantification of spinal curvature in scoliotic radiograph using image processing","volume":"36","author":"H","year":"2012","journal-title":"J. Med. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"E1256","DOI":"10.1097\/BRS.0b013e3182a0c7c3","article-title":"Automatic Cobb angle determination from radiographic images","volume":"38","author":"Sardjono","year":"2013","journal-title":"Spine"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"6357171","DOI":"10.1155\/2019\/6357171","article-title":"Cobb Angle Measurement of Spine from X-Ray Images Using Convolutional Neural Network","volume":"2019","author":"Horng","year":"2019","journal-title":"Comput. Math. Methods Med."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"102115","DOI":"10.1016\/j.media.2021.102115","article-title":"Evaluation and comparison of accurate automated spinal curvature estimation algorithms with spinal anterior-posterior X-Ray images: The AASCE2019 challenge","volume":"72","author":"Wang","year":"2021","journal-title":"Med. Image Anal."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2257","DOI":"10.1007\/s11517-022-02563-7","article-title":"Automatic Cobb angle measurement method based on vertebra segmentation by deep learning","volume":"60","author":"Zhao","year":"2022","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.nec.2012.12.006","article-title":"Adolescent scoliosis classification and treatment","volume":"24","author":"Hoashi","year":"2013","journal-title":"Neurosurg. Clin. N. Am."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1097\/BRS.0b013e3181bf280e","article-title":"A decision tree can increase accuracy when assessing curve types according to Lenke classification of adolescent idiopathic scoliosis","volume":"35","author":"Phan","year":"2010","journal-title":"Spine"},{"key":"ref_44","first-page":"3796202","article-title":"Computerized-Assisted Scoliosis Diagnosis Based on Faster R-CNN and ResNet for the Classification of Spine X-Ray Images","volume":"2022","author":"Chen","year":"2022","journal-title":"Comput. Math. Methods Med."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Yahara, Y., Tamura, M., Seki, S., Kondo, Y., Makino, H., Watanabe, K., Kamei, K., Futakawa, H., and Kawaguchi, Y. (2022). A deep convolutional neural network to predict the curve progression of adolescent idiopathic scoliosis: A pilot study. BMC Musculoskelet. Disord., 23.","DOI":"10.1186\/s12891-022-05565-6"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"101220","DOI":"10.1016\/j.eclinm.2021.101220","article-title":"Application of deep learning upon spinal radiographs to predict progression in adolescent idiopathic scoliosis at first clinic visit","volume":"42","author":"Wang","year":"2021","journal-title":"EClinicalMedicine"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1007\/s11548-011-0667-0","article-title":"A Kohonen neural network description of scoliosis fused regions and their corresponding Lenke classification","volume":"7","author":"Mezghani","year":"2012","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1016\/j.spinee.2013.07.449","article-title":"Artificial neural networks assessing adolescent idiopathic scoliosis: Comparison with Lenke classification","volume":"13","author":"Phan","year":"2013","journal-title":"Spine J."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"16296","DOI":"10.1038\/s41598-018-34261-6","article-title":"Data-driven Classification of the 3D Spinal Curve in Adolescent Idiopathic Scoliosis with an Applications in Surgical Outcome Prediction","volume":"8","author":"Pasha","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1007\/s43390-020-00276-1","article-title":"Discovering the association between the pre- and post-operative 3D spinal curve patterns in adolescent idiopathic scoliosis","volume":"9","author":"Pasha","year":"2021","journal-title":"Spine Deform."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1987","DOI":"10.1007\/s00586-019-06000-6","article-title":"Accurate prediction of spontaneous lumbar curve correction following posterior selective thoracic fusion in adolescent idiopathic scoliosis using logistic regression models and clinical rationale","volume":"28","author":"Koller","year":"2019","journal-title":"Eur. Spine J."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.pediatrneurol.2017.10.019","article-title":"Validation of a Clinical Prediction Model for the Development of Neuromuscular Scoliosis: A Multinational Study","volume":"79","author":"Bertoncelli","year":"2018","journal-title":"Pediatr. Neurol."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.compbiomed.2018.09.029","article-title":"Prediction of spinal curve progression in Adolescent Idiopathic Scoliosis using Random Forest regression","volume":"103","author":"Duong","year":"2018","journal-title":"Comput. Biol. Med."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/S0893-6080(00)00026-5","article-title":"Independent component analysis: Algorithms and applications","volume":"13","author":"Oja","year":"2000","journal-title":"Neural Netw."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1007\/s11548-018-1776-9","article-title":"A deep learning framework for segmentation and pose estimation of pedicle screw implants based on C-arm fluoroscopy","volume":"13","author":"Esfandiari","year":"2018","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"147","DOI":"10.3171\/2018.12.SPINE181397","article-title":"Machine learning for automated 3-dimensional segmentation of the spine and suggested placement of pedicle screws based on intraoperative cone-beam computer tomography","volume":"31","author":"Buerger","year":"2019","journal-title":"J. Neurosurg. Spine"},{"key":"ref_57","first-page":"840","article-title":"Surgical application of pedicle drill template navigation technology for complicated scoliosis","volume":"94","author":"Li","year":"2014","journal-title":"Zhonghua Yi Xue Za Zhi"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"5715","DOI":"10.1002\/mp.15819","article-title":"Deformable 3D-2D image registration and analysis of global spinal alignment in long-length intraoperative spine imaging","volume":"49","author":"Zhang","year":"2022","journal-title":"Med. Phys."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1038\/s41598-020-57693-5","article-title":"Augmented reality navigation with intraoperative 3D imaging vs fluoroscopy-assisted free-hand surgery for spine fixation surgery: A matched-control study comparing accuracy","volume":"10","author":"Fagerlund","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"462875","DOI":"10.1155\/2013\/462875","article-title":"Multiobjective optimization design of spinal pedicle screws using neural networks and genetic algorithm: Mathematical models and mechanical validation","volume":"2013","author":"Amaritsakul","year":"2013","journal-title":"Comput. Math. Methods Med."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.otsr.2019.07.027","article-title":"Patient-specific rods for thoracic kyphosis correction in adolescent idiopathic scoliosis surgery: Preliminary results","volume":"106","author":"Solla","year":"2020","journal-title":"Orthop. Traumatol. Surg. Res."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Tachi, H., Kato, K., Abe, Y., Kokabu, T., Yamada, K., Iwasaki, N., and Sudo, H. (2021). Surgical Outcome Prediction Using a Four-Dimensional Planning Simulation System With Finite Element Analysis Incorporating Pre-bent Rods in Adolescent Idiopathic Scoliosis: Simulation for Spatiotemporal Anatomical Correction Technique. Front. Bioeng. Biotechnol., 9.","DOI":"10.3389\/fbioe.2021.746902"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2350005","DOI":"10.1142\/S0129065723500053","article-title":"A Prediction Model for Normal Variation of Somatosensory Evoked Potential During Scoliosis Surgery","volume":"33","author":"Fei","year":"2023","journal-title":"Int. J. Neural Syst."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Chang, J., Yu, L., Li, Q., Wang, B., Yang, L., Cheng, M., Wang, F., Zhang, L., Chen, L., and Li, K. (2022). Development and Clinical Trial of a New Orthopedic Surgical Robot for Positioning and Navigation. J. Clin. Med., 11.","DOI":"10.3390\/jcm11237091"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1111\/os.12453","article-title":"Guideline for Thoracolumbar Pedicle Screw Placement Assisted by Orthopaedic Surgical Robot","volume":"11","author":"Tian","year":"2019","journal-title":"Orthop. Surg."},{"key":"ref_66","first-page":"1457","article-title":"Study on robot-assisted pedicle screw implantation in adolescent idiopathic scoliosis surgery","volume":"35","author":"Chen","year":"2021","journal-title":"Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"1085580","DOI":"10.3389\/fsurg.2022.1085580","article-title":"Comparison of robot versus fluoroscopy-assisted pedicle screw instrumentation in adolescent idiopathic scoliosis surgery: A retrospective study","volume":"9","author":"Hou","year":"2022","journal-title":"Front. Surg."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1007\/s00586-022-07502-6","article-title":"Accuracy of computer-assisted pedicle screw placement for adolescent idiopathic scoliosis: A comparison between robotics and navigation","volume":"32","author":"Akazawa","year":"2023","journal-title":"Eur. Spine J."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"736","DOI":"10.3171\/2016.10.SPINE16197","article-title":"Development of a preoperative predictive model for major complications following adult spinal deformity surgery","volume":"26","author":"Scheer","year":"2017","journal-title":"J. Neurosurg. Spine"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Peng, L., Lan, L., Xiu, P., Zhang, G., Hu, B., Yang, X., Song, Y., Yang, X., Gu, Y., and Yang, R. (2020). Prediction of Proximal Junctional Kyphosis After Posterior Scoliosis Surgery With Machine Learning in the Lenke 5 Adolescent Idiopathic Scoliosis Patient. Front. Bioeng. Biotechnol., 8.","DOI":"10.3389\/fbioe.2020.559387"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1007\/s00586-018-5816-5","article-title":"Predictive model for major complications 2 years after corrective spine surgery for adult spinal deformity","volume":"28","author":"Yagi","year":"2019","journal-title":"Eur. Spine J."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"587","DOI":"10.3171\/2019.3.SPINE181452","article-title":"Development and validation of risk stratification models for adult spinal deformity surgery","volume":"31","author":"Smith","year":"2019","journal-title":"J. Neurosurg. Spine"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1097\/BRS.0000000000003031","article-title":"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","volume":"44","author":"Ames","year":"2019","journal-title":"Spine"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1998","DOI":"10.1007\/s00586-019-06079-x","article-title":"Development of predictive models for all individual questions of SRS-22R after adult spinal deformity surgery: A step toward individualized medicine","volume":"28","author":"Ames","year":"2019","journal-title":"Eur. Spine J."},{"key":"ref_75","first-page":"i","article-title":"Ethical Issues of Artificial Intelligence in Medicine and Healthcare","volume":"50","author":"Farhud","year":"2021","journal-title":"Iran J. Public Health"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Chen, E., Prakash, S., Janapa Reddi, V., Kim, D., and Rajpurkar, P. (2023). A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring. Nat. Biomed. Eng.","DOI":"10.1038\/s41551-023-01115-0"}],"container-title":["Journal of Clinical Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2077-0383\/12\/23\/7382\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:33:14Z","timestamp":1760131994000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2077-0383\/12\/23\/7382"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,29]]},"references-count":76,"journal-issue":{"issue":"23","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["jcm12237382"],"URL":"https:\/\/doi.org\/10.3390\/jcm12237382","relation":{},"ISSN":["2077-0383"],"issn-type":[{"value":"2077-0383","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,29]]}}}