目的对联合筋膜鞘悬吊术与额肌瓣悬吊术矫正先天性中重度上睑下垂的临床疗效进行对比.方法检索了中英文数据库,中文数据库有万方、维普、中国知网和中国生物医学.英文数据库有Cochrane图书馆、PUBMED和Web of Science网站等.时间为自数...目的对联合筋膜鞘悬吊术与额肌瓣悬吊术矫正先天性中重度上睑下垂的临床疗效进行对比.方法检索了中英文数据库,中文数据库有万方、维普、中国知网和中国生物医学.英文数据库有Cochrane图书馆、PUBMED和Web of Science网站等.时间为自数据库建库以来至2020年5月各数据库所收录的文摘.收集了联合筋膜鞘悬吊术(CFS)与额肌瓣悬吊术矫正先天性中重度上睑下垂术后疗效比较的病例对照研究,严格根据制订的纳入和排除标准筛选文章,选出文章进行治疗评价,确定结局指标并进行数据提取.进行Meta分析所采用的软件是Review Manager 5.3和state 14.0软件.结果共选取了11篇文章,其中296例患者(381眼)为观察组,均采用联合筋膜鞘悬吊术(CFS),291例患者(379眼)为对照组,均采用的是额肌瓣悬吊术.Meta分析结果显示观察组与对照组患者术后矫正率对比的(OR=2.9495%CI:1.94,4.47);术后并发症发生率对比的(OR=0.17,95%CI:0.11,0.27);术后6个月上睑回退量分析结果显示,(WMD=-0.5,95%CI:-0.53,-0.47),结局指标差异均具有统计学意义(P<0.05).结论两种术式治疗上睑下垂疗效都是比较满意的,联合筋膜鞘悬吊术术后矫正率优于额肌瓣悬吊术,且联合筋膜鞘悬吊术后并发症发生率与上睑回退量均低于额肌悬吊术,更为安全,值得在临床上应用并推广.展开更多
Deep learning algorithms increasingly support automated systems in areas such as human activity recognition and purchase recommendation.We identify a current trend in which data is transformed first into abstract visu...Deep learning algorithms increasingly support automated systems in areas such as human activity recognition and purchase recommendation.We identify a current trend in which data is transformed first into abstract visualizations and then processed by a computer vision deep learning pipeline.We call this VisuaLization As Intermediate Representation(VLAIR)and believe that it can be instrumental to support accurate recognition in a number of fields while also enhancing humans’ability to interpret deep learning models for debugging purposes or for personal use.In this paper we describe the potential advantages of this approach and explore various visualization mappings and deep learning architectures.We evaluate several VLAIR alternatives for a specific problem(human activity recognition in an apartment)and show that VLAIR attains classification accuracy above classical machine learning algorithms and several other non-image-based deep learning algorithms with several data representations.展开更多
Osteoarthritis(OA)is mostly considered not a simple cartilage degradation,but a whole joint disorder,with all the joint components involved,such as subchondral bone,synovium and adhesive ligaments/muscles.Moreover,met...Osteoarthritis(OA)is mostly considered not a simple cartilage degradation,but a whole joint disorder,with all the joint components involved,such as subchondral bone,synovium and adhesive ligaments/muscles.Moreover,metabolic syndrome(MetS)and OA are both share a low-grade inflammatory state,and an increasing number of studies have found correlations between metabolic syndrome(MetS)and OA.Their correlations imply that OA might not be a simple joint disorder,but also be affected by MetS.MetS is characterized by a series of risk factors,including hypertension,hyperglycaemia,dyslipidaemia,obesity.However,the findings of some studies didn’t agree with the above correlation between MetS and OA,partly due to complexity of MetS.This review summarizes the correlation between different factors of MetS and OA and the strategic methods for managing MetSrelated OA.Possible mechanisms by which each MetS factor is involved in OA onset and progression are reviewed.This work might help better understand OA and inspire new ideas for preventing and treating OA.展开更多
文摘Deep learning algorithms increasingly support automated systems in areas such as human activity recognition and purchase recommendation.We identify a current trend in which data is transformed first into abstract visualizations and then processed by a computer vision deep learning pipeline.We call this VisuaLization As Intermediate Representation(VLAIR)and believe that it can be instrumental to support accurate recognition in a number of fields while also enhancing humans’ability to interpret deep learning models for debugging purposes or for personal use.In this paper we describe the potential advantages of this approach and explore various visualization mappings and deep learning architectures.We evaluate several VLAIR alternatives for a specific problem(human activity recognition in an apartment)and show that VLAIR attains classification accuracy above classical machine learning algorithms and several other non-image-based deep learning algorithms with several data representations.
基金This work was supported by the National Natural Science Foundation of China(grants 11872076,11472017).
文摘Osteoarthritis(OA)is mostly considered not a simple cartilage degradation,but a whole joint disorder,with all the joint components involved,such as subchondral bone,synovium and adhesive ligaments/muscles.Moreover,metabolic syndrome(MetS)and OA are both share a low-grade inflammatory state,and an increasing number of studies have found correlations between metabolic syndrome(MetS)and OA.Their correlations imply that OA might not be a simple joint disorder,but also be affected by MetS.MetS is characterized by a series of risk factors,including hypertension,hyperglycaemia,dyslipidaemia,obesity.However,the findings of some studies didn’t agree with the above correlation between MetS and OA,partly due to complexity of MetS.This review summarizes the correlation between different factors of MetS and OA and the strategic methods for managing MetSrelated OA.Possible mechanisms by which each MetS factor is involved in OA onset and progression are reviewed.This work might help better understand OA and inspire new ideas for preventing and treating OA.
