[1]Pesapane F,Codari M,Sardanelli F.Artificial intelligence in medical imaging:Threat or opportunity?Radiologists again at the forefront of innovation in medicine[J].Eur Radiol Exp,2018,2(1):35.
[2]Bini SA.Artificial intelligence,machine learning,deep learning,and cognitive computing:what do these terms mean and how will they impact health care?[J].J Arthroplasty,2018,33(8):2358-2361.
[3]Xue Y,Zhang R,Deng Y,et al.A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis[J].PloS One,2017,12(6):e0178992.
[4]Ashinsky BG,Bouhrara M,Coletta CE,et al.Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the osteoarthritis initiative[J].J Orthop Res,2017,35(10):2243-2250.
[5]李旭,肖峰.基于影像特征的膝关节炎进展预测建模及列线图设计[J].湖北大学学报(自然科学版),2022,44(5):609-615.
[6]Smolle MA,Goetz C,Maurer D,et al.Artificial intelligence-based computer-aided system for knee osteoarthritis assessment increases experienced orthopaedic surgeons’ agreement rate and accuracy[J].Knee Surg Sports Traumatol Arthrosc,2023,31(3):1053-1062.
[7]朱士铭,滕伟,李唯,等.基于机器学习算法的影像组学在MRI诊断早期股骨头坏死中的应用[J].中国医学影像学杂志,2021,29(8):817-821.
[8]Klontzas ME,Vassalou EE,Spanakis K,et al.Deep learning enables the differentiation between early and late stages of hip avascular necrosis[J].Eur Radiol,2024,34(2):1179-1186.
[9]Klontzas ME,Manikis GC,Nikiforaki K,et al.Radiomics and machine learning can differentiate transient osteoporosis from avascular necrosis of the hip[J].Diagnostics,2021,11(9):1686.
[10]Yamamoto N,Sukegawa S,Kitamura A,et al.Deep learning for osteoporosis classification using hip radiographs and patient clinical covariates[J].Biomolecules,2020,10(11):1534.
[11]甄涛,胡大成,周健,等.基于多参数MRI影像组学的列线图对膝关节半月板损伤风险度的评估[J].浙江医学,2022,44(14):1506-1512.
[12]Kim S,Kim BR,Chae HD,et al.Deep radiomics-based approach to the diagnosis of osteoporosis using hip radiographs[J].Radiol Artif Intell,2022,4(4):e210212.
[13]Weber M,Renkawitz T,Voellner F,et al.Revision surgery in total joint replacement is cost-intensive[J].Biomed Res Int,2018(2018):8987104.
[14]Giustra F,Bistolfi A,Bosco F,et al.Highly cross-linked polyethylene versus conventional polyethylene in primary total knee arthroplasty:Comparable clinical 〖JP〗and radiological results at a 10-year follow-up[J].Knee Surg Sports Traumatol Arthrosc,2023,31(3):1082-1088.
[15]Borjali A,Chen AF,Muratoglu OK,et al.Detecting mechanical loosening of total hip replacement implant from plain radiograph using deep convolutional neural network[J].J Orthop Res,,2020,38(7):1465-1471.
[16]Lau LCM,Chui ECS,Man GCW,et al.A novel image-based machine learning model with superior accuracy and predictability for knee arthroplasty loosening detection and clinical decision making[J].J Orthop Translat,2022(36):177-183.
[17]Rahman T,Khandakar A,Islam KR,et al.HipXNet:Deep Learning Approaches to Detect Aseptic Loos-Ening of Hip Implants Using X-Ray Images[J].IEEE Access,2022(10):53359-53373.
[18]Delanois RE,Mistry JB,Gwam CU,et al.Current epidemiology of revision total knee arthroplasty in the United States[J].J Arthroplasty,2017,32(9):2663-2668.
[19]Albano D,Gitto S,Messina C,et al.MRI-based artificial intelligence to predict infection following total hip arthroplasty failure[J].Radiol Med,2023,128(3):340-346.
[20]Tan TL,Maltenfort MG,Chen AF,et al.Development and evaluation of a preoperative risk calculator for periprosthetic joint infection following total joint arthroplasty[J].J Bone Joint Surg(Am),2018,100(9):777-785.
[21]Berbari EF,Osmon DR,Lahr B,et al.The Mayo prosthetic joint infection risk score:Implication for surgical site infection reporting and risk stratification[J].Infect Control Hosp Epidemiol,2012,33(8):774-781.
[22]Klemt C,Yeo I,Harvey M,et al.The use of artificial intelligence for the prediction of periprosthetic joint infection following aseptic revision total knee arthroplasty[J].J Knee Surg,2024,37(2):158-166.
[23]李欣,雷孝勇,康大为.全髋关节置换术后假体周围发生骨折的列线图预测模型构建和评估[J].中国骨伤,2023,36(11):1036-1040.
[24]徐青,余冰,周佩敏,等.基于机器学习与SHAP的全髋关节置换术患者下肢深静脉血栓可解释性预测模型构建研究[J].中国医院统计,2024,31(1):11-18;24.
[25]Berstock JR,Beswick AD,Lenguerrand E,et al.Mortality after total hip replacement surgery:A systematic review[J].Bone Joint Res,2014,3(6):175-182.
[26]李志鹏,环大维,袁兆丰,等.老年股骨颈骨折患者术后死亡的危险因素及预测列线图的构建[J].中国组织工程研究,2024,28(21):3361-3366.
[27]Hunt LP,Ben-Shlomo Y,Clark EM,et al.90-day mortality after 409 096 total hip replacements for osteoarthritis,from the national joint registry for England and Wales:A retrospective analysis[J].Lancet,2013,382(9898):1097-1104.
[28]Runner RP,Bellamy JL,Vu CPCL,et al.Modified frailty index is an effective risk assessment tool in primary total knee arthroplasty[J].J Arthroplasty,2017,32(9):S177-S182.
[29]Harris AHS,Kuo AC,Weng Y,et al.Can machine learning methods produce accurate and easy-to-use prediction models of 30-day complications and mortality after knee or hip arthroplasty?[J].Clin Orthop Relat Res,2019,477(2):452.
[30]Subramaniam S,Aalberg JJ,Soriano RP,et al.New 5-factor modified frailty index using American college of surgeons NSQIP data[J].J Am Coll Surg,2018,226(2):173-181.
[31]Traven SA,Reeves RA,Sekar MG,et al.New 5-factor modified frailty index predicts morbidity and mortality in primary hip and knee arthroplasty[J].J Arthroplasty,2019,34(1):140-144.
[32]Abraham VM,Booth G,Geiger P,et al.Machine-learning models predict 30-day mortality,cardiovascular complications,and respiratory complications after aseptic revision total joint arthroplasty〖JP〗[J].Clin Orthop Relat Res,2022,480(11):2137-2145.
[33]Raad M,Amin R,Puvanesarajah V,et al.The CARDE-B scoring system predicts 30-day mortality after revision total joint arthroplasty[J].J Bone Joint Surg(Am),2021,103(5):424.
[34]Digioia AM,Jaramaz B,Colgan BD.Computer assisted orthopaedic surgery.Image guided and robotic assistive technologies[J].Clin Orthop Relat Res,1998(354):8-16.
[35]Hu X,Nguyen A,Baena FRY.Occlusion-robust visual markerless bone tracking for computer-assisted orthopaedic surgery[J].IEEE Transactions on Instrumentation and Measurement,2022(71):1-11.
[36]Nich C,Behr J,Crenn V,et al.Applications of artificial intelligence and machine learning for the hip and knee surgeon:Current state and implications for the future[J].Int Orthop,2022,46(5):937-944.
[37]Habehh H,Gohel S.Machine learning in healthcare[J].Curr Genomics,2021,22(4):291.