[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125186-en":3,"doc-seo-125186-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125186,1374391975076,"Riley","https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051",8,"Research & Report","Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning - Original Research","This original research develops machine learning models to predict short-term postoperative neurological outcomes in patients with degenerative cervical myelopathy (DCM) after surgical decompression. A retrospective cohort of 1,895 patients was reviewed, with 672 included in the final analysis. Five algorithms were trained to predict achieving the minimal clinically important difference (MCID) in Japanese Orthopedic Association (JOA) score, using baseline, clinical, physical examination, T2WI MRI signals, and scale measures. The best-performing LightGBM model was validated on an external dataset and identified key prognostic features.","TYPE Original Research PUBLISHED 04 March 2025  \nDOI 10.3389/fbioe.2025.1529545  \nOPEN ACCESS  \nEDITED BY  \nLianlei Wang,  \nShandong University, China  \nREVIEWED BY  \nTakashi Kaito,  \nOsaka University, Japan Mo Li,  \nThe First Affiliated Hospital of Air Force Medical University, China  \n*CORRESPONDENCE  \nHong Ji,  \n [ji_hong@126.com](ji_hong@126.com)[ ](ji_hong@126.com)Feifei Zhou,  \n [orthozhou@163.com](orthozhou@163.com)  \n†These authors have contributed equally to this work  \nRECEIVED 17 November 2024  \nACCEPTED 30 January 2025  \nPUBLISHED 04 March 2025  \nCITATION  \nZhou S, Liu Z, Huang H, Xi H, Fan X, Zhao Y, Chen X, Diao Y, Sun Y, Ji H and Zhou F (2025) Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning.  \nFront. Bioeng. Biotechnol. 13:1529545 .  \ndoi: 10.3389/fbioe.2025.1529545  \nCOPYRIGHT  \n© 2025 Zhou, Liu, Huang, Xi, Fan, Zhao, Chen, Diao, Sun, Ji and Zhou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nPredicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning  \nShuai Zhou 1,2,3,4†, Zexiang Liu 1,2,3†, Haoge Huang 1,2,3†, Hanxu Xi 5, Xiao Fan 1,2,3, Yanbin Zhao 1,2,3, Xin Chen 1,2,3, Yinze Diao 1,2,3, Yu Sun 1,2,3, Hong Ji 5* and Feifei Zhou 1,2,3*  \n1Department of Orthopaedics, Peking University Third Hospital, Beijing, China, 2Engineering Research Center of Bone and Joint Precision Medicine, Ministry of Education, Beijing, China, 3Beijing Key Laboratory of Spinal Disease Research, Beijing, China, 4Department of Orthopaedics, China Emergency General Hospital, Beijing, China, 5Information Management and Big Data Center, Peking University Third Hospital, Beijing, China  \nIntroduction: This study aimed to develop machine learning models to predict neurological outcomes in patients with degenerative cervical myelopathy (DCM) after surgical decompression and identify key factors that contribute to a better outcome, providing a reference for patient consultation and surgical decision-making.  \nMethods: This retrospective study reviewed 1,895 patients who underwent cervical decompression surgery for DCM at Peking University Third Hospital from 2011 to 2020, with 672 patients included in the final analysis. Five machine learning methods, namely, linear regression (LR), support vector machines (SVM), random forest (RF), XGBoost, and Light Gradient Boosting Machine (LightGBM), were used to predict whether patients achieved the minimal clinically important difference (MCID) in the improvement in the Japanese Orthopedic Association (JOA) score, which was based on basic information, symptoms, physical examination signs, intramedullary high signals on T2-weighted (T2WI) magnetic resonance imaging (MRI), and various scale scores. After training and optimizing multiple ML algorithms, we generated a model with the highest area under the receiver operating characteristic curve (AUROC) to predict short-term outcomes following DCM surgery. We evaluated the importance of the features and created a feature-reduced model. The model’s performance was assessed using an external dataset.  \nResults: The LightGBM algorithm performed the best in predicting short-term neurological outcomes in the testing dataset, achieving an AUROC value of 0.745 and an area under the precision–recall curve (AUPRC) value of 0 .810. The important features influencing performance in the short-term model included the preoperative JOA score, age, SF-36-GH, SF-36-BP, and SF-36-PF. The feature-reduced LightGBM model, which achieved an AUROC value of 0.734, also showed","cbCailPKZCl4W4L7","https://ap.wps.com/l/cbCailPKZCl4W4L7","pdf",1864883,1,11,"English","en",105,"# Introduction\n## Methods\n## Results\n## Conclusion","[{\"question\":\"What is the primary goal of this study on degenerative cervical myelopathy?\",\"answer\":\"To develop machine learning models that predict postoperative neurological outcomes after surgical decompression and identify important factors linked to better results.\"},{\"question\":\"How were the prediction models evaluated?\",\"answer\":\"Models were trained and optimized using retrospective data, with performance assessed using an external dataset and metrics including AUROC and AUPRC for short-term outcomes.\"},{\"question\":\"Which algorithm performed best for short-term neurological outcome prediction?\",\"answer\":\"LightGBM achieved the highest performance in the testing dataset, with AUROC of 0.745 and AUPRC of 0.810.\"}]","Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning - Original Research | PDF",1785897266,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"predicting-postoperative-neurological-outcomes-of-degenerative-cervical-myelopathy-based-on-machine-learning-original-research","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/predicting-postoperative-neurological-outcomes-of-degenerative-cervical-myelopathy-based-on-machine-learning-original-research/125186/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the primary goal of this study on degenerative cervical myelopathy?","Question",{"text":75,"@type":76},"To develop machine learning models that predict postoperative neurological outcomes after surgical decompression and identify important factors linked to better results.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were the prediction models evaluated?",{"text":80,"@type":76},"Models were trained and optimized using retrospective data, with performance assessed using an external dataset and metrics including AUROC and AUPRC for short-term outcomes.",{"name":82,"@type":73,"acceptedAnswer":83},"Which algorithm performed best for short-term neurological outcome prediction?",{"text":84,"@type":76},"LightGBM achieved the highest performance in the testing dataset, with AUROC of 0.745 and AUPRC of 0.810.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]