参考文献/References:
[1] Buch VH,Ahmed I,Maruthappu M.Artificial intelligence in medicine:current trends and future possibilities[J].Br J Gen Pract,2018,68(668):143-144.DOI:10.3399/bjgp18X695213.
[2] Kirk B,Zanker J,Duque G.Osteosarcopenia:epidemiology,diagnosis,and treatment-facts and numbers[J].J Cachexia Sarcopenia Muscle,2020,11(3):609-618.DOI:10.1002/jcsm.12567.
[3] Exton-Smith AN,Millard PH,Payne PR,et al.Method for measuring quantity of bone[J].Lancet,1969,2(7631):1153-1154.DOI:10.1016/s0140-6736(69)92482-9.
[4] Narla RR,Ott SM.Structural and metabolic assessment of bone[J].Handb Exp Pharmacol,2020,262:369-396.DOI:10.1007/164_2020_376
[5] Sollmann N,Löffler MT,Kronthaler S,et al.MRI-based quantitative osteoporosis imaging at the spine and femur[J].J Magn Reson Imaging,2021,54(1):12-35.DOI:10.1002/jmri.27260.
[6] Issayeva S,Lesnyak O,Zakroyeva A,et al.Epidemiology of osteoporotic fracture in Kazakhstan and development of a country specific FRAX model[J].Arch Osteoporos,2020,15(1):30.DOI:10.1007/s11657-020-0701-3.
[7] Curtis EM,Moon RJ,Harvey NC,et al.The impact of fragility fracture and approaches to osteoporosis risk assessment worldwide[J].Bone,2017,104:29-38.DOI:10.1016/j.bone.2017.01.024.
[8] Damron TA,Mann KA.Fracture risk assessment and clinical decision making for patients with metastatic bone disease[J].J Orthop Res,2020,38(6):1175-1190.DOI:10.1002/jor.24660.
[9] Martineau P,Leslie WD.The utility and limitations of using trabecular bone score with FRAX[J].Curr Opin Rheumatol,2018,30(4):412-419.DOI:10.1097/BOR.0000000000000504.
[10] Hussain A,Al-Jumeily D,Aljaaf A,et al.Backpropagation approach supported by image compression algorithm for the classification of chronic condition diseases[J].IEEE/ACM Trans Comput Biol Bioinform,2018,PP:1-1.DOI:10.1109/TCBB.2018.2878556.
[11] Zhou K,Wang W,Hu T,et al.Time series forecasting and classification models based on recurrent with attention mechanism and generative adversarial networks[J].Sensors(Basel),2020,20(24):7211.DOI:10.3390/s20247211.
[12] Esteva A,Robicquet A,Ramsundar B,et al.A guide to deep learning in healthcare[J].Nat Med,2019,25(1):24-29.DOI:10.1038/s41591-018-0316-z.
[13] Ongphiphadhanakul B,Rajatanavin R,Chailurkit L,et al.Prediction of low bone mineral density in postmenopausal women by artifcial neural network model compared to logistic regression model[J].J Med Assoc Thai,1997,80:508-515.
[14] Kung AW,Ho AY,Sedrine WB,et al.Comparison of a simple clinical risk index and quantitative bone ultrasound for identifying women at increased risk of osteoporosis[J].Osteoporos Int,2003,14(9):716-721.DOI:10.1007/s00198-003-1428-x.
[15] Wang W,Richards G,Rea S.Hybrid data mining ensemble for predicting osteoporosis risk[J].Conf Proc IEEE Eng Med Biol Soc,2005,2006:886-889.DOI:10.1109/IEMBS.2005.1616557.
[16] Ho-Le TP,Center JR,Eisman JA,et al.Prediction of hip fracture in post-menopausal women using artificial neural network approach[J].Annu Int Conf IEEE Eng Med Biol Soc,2017,2017:4207-4210.DOI:10.1109/EMBC.2017.8037784.
[17] Lee S,Lee JW,Jeong JW,et al.A preliminary study on discrimination of osteoporotic fractured group from nonfractured group using support vector machine[J].Annu Int Conf IEEE Eng Med Biol Soc,2008,2008:474-477.DOI:10.1109/IEMBS.2008.4649193.
[18] Juez F,Suárez-Suárez MA,Lasheras FS,et al.Application of neural networks to the study of the infuence of diet and lifestyle on the value of bone mineral density in post-menopausal women[J].Mathemat Comput Modelling,2011,54(7-8):1665-1670.DOI:10.1016/j.mcm.2010.11.069.
[19] Harrar K,Hamami L,Akkoul S,et al.Osteoporosis assessment using multilayer perceptron neural networks[J].IEEE,2012,217-21.DOI:10.1109/IPTA.2012.6469528.
[20] Villamor E,Monserrat C,Del Río L,et al.Prediction of osteoporotic hip fracture in postmenopausal women through patient-specific FE analyses and machine learning[J].Comput Methods Programs Biomed,2020,193:105484.DOI:10.1016/j.cmpb.2020.105484.
[21] Hwang JJ,Lee JH,Han SS,et al.Strut analysis for osteoporosis detection model using dental panoramic radiography[J].Dentomaxillofac Radiol,2017,46(7):20170006.DOI:10.1259/dmfr.20170006.
[22] Iliou T,Anagnostopouls CN, Stephanalkis IM,et al.A novel data preprocessing method for boosting neural network performance:a case study in osteoporosis prediction[J].Inf Sci,2017,380(Suppl C):92-100.DOI:10.1016/j.ins.2015.10.026.
[23] Liu Q,Cui X,Chou YC,et al.Ensemble artifcial neural networks applied to predict the key risk factors of hip bone fracture for elders[J].Biomed Signal Process Control,2015,21(4):146-156.DOI:10.1016/j.bspc.2015.06.002.
[24] Yu X,Ye C,Xiang L.Application of artifcial neural network in the diagnostic system of osteoporosis[J].Neurocomputing,2016,214(19):376-381.DOI:10.1016/j.neucom.2016.06.023.
相似文献/References:
[1]赵一璟 王昆 刘超.噻唑烷二酮类药物临床实用价值和安全性的再认识[J].国际内分泌代谢杂志,2019,39(04):236.[doi:10.3760/cma.j.issn.1673-4157.2019.04.005]
Zhao Yijing,Wang Kun,Liu Chao.Reconsideration of the efficacy and safety of thiazolidinediones[J].International Journal of Endocrinology and Metabolism,2019,39(04):236.[doi:10.3760/cma.j.issn.1673-4157.2019.04.005]
[2]董荣娜,李晶.人工智能在糖尿病视网膜病变诊断中应用的研究进展[J].国际内分泌代谢杂志,2020,40(06):412.[doi:10.3760/cma.j.cn121383-20200328-03075]
Dong Rongna,Li Jing.Advances in the application of artificial intelligence in the diagnosis of diabetic retinopathy[J].International Journal of Endocrinology and Metabolism,2020,40(04):412.[doi:10.3760/cma.j.cn121383-20200328-03075]
[3]谭晓霞,张帆.糖尿病微血管病变合并骨质疏松症的研究进展[J].国际内分泌代谢杂志,2021,41(01):48.[doi:10.3760/cma.j.cn121383-20200420-04053]
Tan Xiaoxia,Zhang Fan..Research progress on diabetic microangiopathy complicated with osteoporosis[J].International Journal of Endocrinology and Metabolism,2021,41(04):48.[doi:10.3760/cma.j.cn121383-20200420-04053]
[4]吴晗 于淼 贾黎静 肖诚.遗传性血色病所致内分泌功能异常的研究进展[J].国际内分泌代谢杂志,2023,43(05):376.[doi:10.3760/cma.j.cn121383-20221211-12028]
Wu Han,Yu Miao,Jia Lijing,et al.Research advances in endocrinopathies caused by hereditary haemochromatosis[J].International Journal of Endocrinology and Metabolism,2023,43(04):376.[doi:10.3760/cma.j.cn121383-20221211-12028]
[5]樊淑娟,代青湘.高血压与骨质疏松症相关机制研究进展[J].国际内分泌代谢杂志,2023,43(06):489.[doi:10.3760/cma.j.cn121383-20220511-05019]
Fan Shujuan,Dai Qingxiang..Research progress on the correlation mechanism between hypertension and osteoporosis[J].International Journal of Endocrinology and Metabolism,2023,43(04):489.[doi:10.3760/cma.j.cn121383-20220511-05019]