缺乏囊膜支持的无晶状体眼中两种人工晶状体植入方式的疗效比较

目的:在缺少囊膜支撑的无晶状体眼中,比较后房植入虹膜夹人工晶状体(IOL)与后房睫状沟巩膜缝合固定人工晶状体的疗效。方法:本研究收集缺少囊膜支撑的无晶状体患者70例进行回顾性对比分析,患者根据手术方式的不同分为A、B两组,A组35眼行后房植入虹膜夹IOL,B组35眼行后房睫状沟巩膜缝合固定IOL。比较两组患者术前及术后3d,1、3、6mo,1a的裸眼视力(UCVA)、最佳矫正视力(BCVA)、眼压(IOP)、角膜内皮细胞密度(CECD),并且观察两组IOL的稳定性,记录术中及术后并发症。结果:随访12~14mo。术后3d,A组的UCVA较术前明显改善(P<0.01),而BCVA较术前无差异(P=0.073);B组的UCVA较术前无差异(P=0.097),而BCVA较术前差(P=0.002);两组患者术后1mo UCVA、BCVA均较术前显著改善(P<0.05),分别于术后6、3mo保持稳定。两组患者随访期间的IOP均维持于正常水平。A组、B组患者术后1a的CECD分别较术前平均降低0.7%、2.3%(均P<0.05)。两组患者随访期间各时间点IOP及CECD的均无差异(P>0.05)。两组患者术后1、3mo的全眼散光较角膜散光无明显差异(均P>0.05)。术后两组各有1眼IOL脱位,均经手术复位,其余患者术后随访期间IOL无显著倾斜和偏位;其他术后并发症较轻微,组间并发症发生率无差异(P>0.05)。结论:对于缺少囊膜支持的无晶状体眼患者,后房植入虹膜夹IOL与后房睫状沟巩膜缝合固定IOL均是安全有效的手术方式。后房植入虹膜夹IOL的操作相对简单,对眼球内组织损伤较小,手术时间较短,术后视力恢复较快,是有效的治疗方法之一。

Exploiting Unlabeled Data for Neural Grammatical Error Detection

Identifying and correcting grammatical errors in the text written by non-native writers have received increasing attention in recent years. Although a number of annotated corpora have been established to facilitate data-driven grammatical error detection and correction approaches, they are still limited in terms of quantity and coverage because human annotation is labor-intensive, time-consuming, and expensive. In this work, we propose to utilize unlabeled data to train neural network based grammatical error detection models. The basic idea is to cast error detection as a binary classification problem and derive positive and negative training examples from unlabeled data. We introduce an attention-based neural network to capture long-distance dependencies that influence the word being detected. Experiments show that the proposed approach significantly outperforms SVM and convolutional networks with fixed-size context window.