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BACKGROUND:Based on different algorithms of machine learning,how to carry out clinical research on lumbar disc herniation with the help of various algorithmic models has become a trend and hot spot in the development of intelligent medicine at present. OBJECTIVE:To review the characteristics of different algorithmic models of machine learning in the diagnosis and treatment of lumbar disc herniation,and summarize the respective advantages and application strategies of algorithmic models for the same purpose. METHODS:The computer searched PubMed,Web of Science,EMBASE,CNKI,WanFang,VIP and China Biomedical(CBM)databases to extract the relevant articles on machine learning in the diagnosis and treatment of lumbar disc herniation.Finally,96 articles were included for analysis. RESULTS AND CONCLUSION:(1)Different algorithm models of machine learning provide intelligent and accurate application strategies for clinical diagnosis and treatment of lumbar disc herniation.(2)Traditional statistical methods and decision trees in supervised learning are simple and efficient in exploring risk factors and establishing diagnostic and prognostic models.Support vector machine is suitable for small data sets with high-dimensional features.As a nonlinear classifier,it can be applied to the recognition,segmentation and classification of normal or degenerative intervertebral discs,and to establish diagnostic and prognostic models.Ensemble learning can make up for the shortcomings of a single model.It has the ability to deal with high-dimensional data and improve the precision and accuracy of clinical prediction models.Artificial neural network improves the learning ability of the model,and can be applied to intervertebral disc recognition,classification and making clinical prediction models.On the basis of the above uses,deep learning can also optimize images and assist surgical operations.It is the most widely used model with the best performance in the diagnosis and treatment of lumbar disc herniation.The clustering algorithm in unsupervised learning is mainly used for disc segmentation and classification of different herniated segments.However,the clinical application of semi-supervised learning is relatively less.(3)At present,machine learning has certain clinical advantages in the identification and segmentation of lumbar intervertebral discs,classification and grading of the degenerative intervertebral discs,automatic clinical diagnosis and classification,construction of the clinical predictive model and auxiliary operation.(4)In recent years,the research strategy of machine learning has changed to the neural network and deep learning,and the deep learning algorithm with stronger learning ability will be the key to realizing intelligent medical treatment in the future.
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BACKGROUND:Anterior cruciate ligament rupture is one of the injuries that seriously affect life and sports performance,and the anterior cruciate ligament as a stabilizing structure is irreplaceable in maintaining sports performance.In view of its severe injury manifestations,the current treatment for anterior cruciate ligament rupture is a surgery for anterior cruciate ligament reconstruction.Since an anterior cruciate ligament injury can cause loss of mechanoreceptors,which in turn causes a reduction in proprioception,it is a great problem for patients to recover their motor performance. OBJECTIVE:To summarize the effects of proprioceptive training on clinical outcomes after anterior cruciate ligament reconstruction and to explore the underlying mechanisms,thereby providing more references for clinical prevention and treatment. METHODS:A computerized search of PubMed,CNKI,WanFang Data,and VIP databases was conducted for literature(from January 2013 to March 2023)related to proprioceptive training after anterior cruciate ligament reconstruction that improves joint stability and motor balance ability.A total of 108 articles were finally included for review. RESULTS AND CONCLUSION:Proprioceptive training can effectively improve the proprioceptive functions of patients,such as positional sense and kinesthetic sense after anterior cruciate ligament reconstruction,and improve joint stability,postural control and motor ability.The proprioceptive training improves the proprioceptive function through three mechanisms:stimulation of periprosthetic receptors around the knee joint,activation of spinal reflex stimulation,reinforcement of motor control in the brain,and enhancement of cognitive processing.The proprioceptive training may improve proprioceptive functions by activating the potential mechanisms of growth associated protein-43 activity,Piezo2 mechanotransducer,and NT-3/TrkC signaling pathway.Hydrotherapy is the mainstay in the early stages,while neuromuscular training,individual strength training and visual feedback training are prioritized in the middle and late stages.There exists an as-yet-unsegmented reconstructive surgery graft,sex,and a lack of devices or proprioceptive training methods based on the idea of combining multiple sensory stimuli.
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BACKGROUND:In recent years,epidemiological studies have shown that sleep patterns are risk factors for osteoarthritis,but the causal relationship between sleep characteristics and osteoarthritis remains unknown. OBJECTIVE:To investigate the causal relationship between seven sleep phenotypes and osteoarthritis,thereby providing a theoretical foundation for clinical prevention and intervention of osteoarthritis. METHODS:Seven sleep-related features,namely sleep duration,wake-up time,daytime napping,morning/evening preference,snoring,insomnia,and hypersomnia,were selected from published genome-wide association studies.Instrumental variables for these sleep-related features were extracted.Instrumental variables for knee osteoarthritis and hip osteoarthritis were obtained from publicly available genome-wide association studies.Causal relationships between sleep characteristics and outcome risks were evaluated using two-sample and multivariable Mendelian randomization analyses.The inverse variance weighted method was employed as the primary Mendelian randomization approach.Various methods,including weighted median,weighted mode,Mendelian randomization-Egger regression,Mendelian randomization pleiotropy-residual sum and outlier,were utilized to detect and correct for the presence of pleiotropy. RESULTS AND CONCLUSION:The results of the inverse variance-weighted method in the two-sample Mendelian randomization study revealed a detrimental causal association between the duration of sleep and the incidence risk of knee osteoarthritis[odds ratio(OR)=0.621,95%confidence interval(CI):0.470-0.822,P=0.001].Concurrently,insomnia displayed a positive causal connection with hip osteoarthritis risk(OR=2.016,95%CI:1.249-3.254,P=0.005).Sensitivity analysis affirmed the robustness of these causal relationships,and Mendelian randomization-Egger intercept analysis found no evidence of potential horizontal pleiotropy(knee osteoarthritis:P=0.468,hip osteoarthritis:P=0.551).Moreover,the results from the multivariable Mendelian randomization analysis showed that the causal association between insomnia and hip osteoarthritis lacked statistical significance(P=0.715).In contrast,sleep duration exhibited a direct negative causal relationship with the incidence risk of knee osteoarthritis(OR=0.526,95%CI:0.336-0.824,P=0.005).Reverse Mendelian randomization analysis indicated that knee osteoarthritis did not influence sleep duration(P=0.757).These findings indicate a negative correlation between sleep duration and incidence risk of knee osteoarthritis,suggesting that correcting insufficient sleep might mitigate the incidence risk of knee osteoarthritis.
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Knee osteoarthritis (KOA) is a kind of degenerative osteoarthrosis, which usually involves articular cartilage, subchondral bone, meniscus and quadriceps femoris, which is equivalent to the change of "tendon" in traditional Chinese medicine. The occurrence and development of the change of "tendon" can be explained by the theory of "bone-restoration and tendon-softening" in traditional Chinese medicine. If the force line of the lower limb of the knee joint is normal, it can be indicated by "bone-restoration" in traditional Chinese medicine, that is, the blood around the knee joint runs smoothly, and the "tenons" such as meniscus, ligaments, cartilage, etc. are softened by the blood. This condition of the knee joint can be manifested by the balance of the surrounding soft tissue state. If the force line of the lower limb of the knee joint changes, showing a medial offset and misalignment of the knee joint, it can be indicated by "bone is out of alignment" in traditional Chinese medicine, that is, the structure of the soft tissue around the knee joint and its mechanical characteristics have changed. This condition of the knee joint can be manifested by "the tendons lose their flexibility". In this paper, the theories of modern biomechanics and "bone-restoration and tendon-softening" in traditional Chinese medicine were comprehensively analyzed, the characteristics of the "tenons" when knee osteoarthritis occurs were analyzed, and the characteristics of the occurrence and development of knee osteoarthritis from the perspective of Chinese and Western medicine were discussed.