A Comparison of Artificial Intelligence and Human Diabetic Retinal Image Interpretation in an Urban Health System

Introduction:Artificial intelligence (AI) diabetic retinopathy (DR) software has the potential to decrease time spent by clinicians on image interpretation and expand the scope of DR screening. We performed a retrospective review to compare Eyenuk’s EyeArt software (Woodland Hills, CA) to Temple Ophthalmology optometry grading using the International Classification of Diabetic Retinopathy scale.Methods:Two hundred and sixty consecutive diabetic patients from the Temple Faculty Practice Internal Medicine clinic underwent 2-field retinal imaging. Classifications of the images by the software and optometrist were analyzed using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and McNemar’s test. Ungradable images were analyzed to identify relationships with HbA1c, age, and ethnicity. Disagreements and a sample of 20% of agreements were adjudicated by a retina specialist.Results:On patient level comparison, sensitivity for the software was 100%, while specificity was 77.78%. PPV was 19.15%, and NPV was 100%. The 38 disagreements between software and optometrist occurred when the optometrist classified a patient’s images as non-referable while the software classified them as referable. Of these disagreements, a retina specialist agreed with the optometrist 57.9% the time (22/38). Of the agreements, the retina specialist agreed with both the program and the optometrist 96.7% of the time (28/29). There was a significant difference in numbers of ungradable photos in older patients (≥60) vs younger patients (<60) (p=0.003).Conclusions:The AI program showed high sensitivity with acceptable specificity for a screening algorithm. The high NPV indicates that the software is unlikely to miss DR but may refer patients unnecessarily.     

Titanium-Pillared Clay: Preparation Optimization,Characterization, and Artificial Neural Network Modeling

Titanium-pillared clay (Ti-PILC), as one of the most suitable types of porous adsorbents/(photo)catalysts, was prepared from a local type of Iranian clay and titanium isopropoxide. The production process was optimized by changing three operating parameters, including the clay suspension concentration (in the range of 0.5–10% w/v), the H⁺/Ti ratio (2–8 mol/mol), and the calcination temperature (300–700 °C). The largest specific surface area for the Ti-PILC was about 164 m²/g under the clay suspension of 0.5% w/v, H⁺/Ti = 6, with a surface area 273% larger than that of the raw clay. The surface areas obtained from more concentrated clay suspensions were, however, comparable (159 m²/g for 3% w/v clay and H⁺/Ti = 4). An increase in the calcination temperature has a negative effect on the porous texture of Ti-PILC, but based on modeling with artificial neural networks, its contribution was only 7%. Clay suspension and H⁺/Ti ratio play a role of 56 and 37% of the specific surface area. The presence of rutile phase, and in some cases anatase phase of TiO₂ crystals was detected. FTIR and SEM investigations of Ti-PILCs produced under different operating parameters were analyzed.     

大鼠坐骨神经缺损半个月后人工组织神经移植物修复的实验研究

为了观察人工组织神经移植物对大鼠坐骨神经非新鲜损伤的修复作用。我们在成年SD大鼠左侧股中部切除部分坐骨神经制造神经缺损模型。15d后,实验组(9只)用人工组织神经移植物修复神经缺损,自体神经修复作为阳性对照(6只),保持神经缺损为阴性对照(6只)。第二次手术后3个月,电生理学、形态学结果显示实验组的再生神经虽略差于自体对照组,但明显优于缺损对照组,腓肠肌的萎缩形态学指标变化则较接近自体对照组。实验结果表明人工组织神经移植物对已缺损15d的大鼠周围神经具有较好修复作用。     

肺癌免疫治疗中分离反应的研究进展

肺癌是世界上最常见的恶性肿瘤之一,也是全球癌症死亡的主要原因[1]。近年来,随着免疫检查点抑制剂(immune checkpoint inhibitors,ICIs) 的应用、发展与兴起,一小部分晚期非小细胞肺癌(non-small cell lung cancer,NSCLC) 患者可从中获益。随着对ICIs药物应用后治疗效果的观察,与化疗药物及靶向药物可引起的典型反应,包括完全缓解(complete response,CR)、部分缓解(partial response,PR)、疾病稳定(stable disease,SD)、疾病进展(progressive disease,PD)比较,ICIs可引起另一种非典型反应模式,包括超进展、假性进展、分离反应等。与前两种非典型反应模式比较,目前的研究数据对分离反应的研究报道相对较少。本文回顾一些分离反应的研究,探讨其意义并思考其后续治疗方法。     

Multi-population generalizability of a deep learning-based chest radiograph severity score for COVID-19

To tune and test the generalizability of a deep learning-based model for assessment of COVID-19 lung disease severity on chest radiographs (CXRs) from different patient populations.A published convolutional Siamese neural network-based model previously trained on hospitalized patients with COVID-19 was tuned using 250 outpatient CXRs. This model produces a quantitative measure of COVID-19 lung disease severity (pulmonary x-ray severity (PXS) score). The model was evaluated on CXRs from 4 test sets, including 3 from the United States (patients hospitalized at an academic medical center (N = 154), patients hospitalized at a community hospital (N = 113), and outpatients (N = 108)) and 1 from Brazil (patients at an academic medical center emergency department (N = 303)). Radiologists from both countries independently assigned reference standard CXR severity scores, which were correlated with the PXS scores as a measure of model performance (Pearson R). The Uniform Manifold Approximation and Projection (UMAP) technique was used to visualize the neural network results.Tuning the deep learning model with outpatient data showed high model performance in 2 United States hospitalized patient datasets (R = 0.88 and R = 0.90, compared to baseline R = 0.86). Model performance was similar, though slightly lower, when tested on the United States outpatient and Brazil emergency department datasets (R = 0.86 and R = 0.85, respectively). UMAP showed that the model learned disease severity information that generalized across test sets.A deep learning model that extracts a COVID-19 severity score on CXRs showed generalizable performance across multiple populations from 2 continents, including outpatients and hospitalized patients.     

关节镜辅助复位内固定与切开复位内固定治疗胫骨平台骨折的疗效比较

目的:比较关节镜辅助复位内固定（ARIF）和切开复位内固定（ORIF）治疗胫骨平台骨折的疗效。方法:回顾性分析2016年1月至2018年8月华中科技大学附属协和医院骨科收治的75例胫骨平台骨折患者的资料。男58例,女17例;年龄20~54岁,平均47岁。左侧42例,右侧33例。骨折根据Schatzker分型：Ⅰ型23例...     

复合陶瓷人工全踝关节的研制及临床应用

本文介绍了研制的复合陶瓷人工踝关节,并讨论了踝关节生物力学特点,假体设计的生物力学依据和临床应用效果及其设计依据。     

Predicting Compressive and Splitting Tensile Strengths of Silica Fume Concrete Using M5P Model Tree Algorithm

Compressive strength (CS) and splitting tensile strength (STS) are paramount parameters in the design of reinforced concrete structures and are required by pertinent standard provisions. Robust prediction models for these properties can save time and cost by reducing the number of laboratory trial batches and experiments needed to generate suitable design data. Silica fume (SF) is often used in concrete owing to its substantial enhancements of the engineering properties of concrete and its environmental benefits. In the present study, the M5P model tree algorithm was used to develop models for the prediction of the CS and STS of concrete incorporating SF. Accordingly, large databases comprising 796 data points for CS and 156 data records for STS were compiled from peer-reviewed published literature. The predictions of the M5P models were compared with linear regression analysis and gene expression programming. Different statistical metrics, including the coefficient of determination, correlation coefficient, root mean squared error, mean absolute error, relative squared error, and discrepancy ratio, were deployed to appraise the performance of the developed models. Moreover, parametric analysis was carried out to investigate the influence of different input parameters, such as the SF content, water-to-binder ratio, and age of the specimen, on the CS and STS. The trained models offer a rapid and accurate tool that can assist the designer in the effective proportioning of silica fume concrete.     

喉功能保留外科相关的喉功能解剖

目的 了解喉功能的解剖学基础,为喉癌、下咽癌手术保留喉功能提供解剖依据.方法 对4例成年男性尸体喉部的环杓关节相关肌肉、神经及血管进行解剖观察,根据肌肉的起止点与肌纤维方向分析各肌肉的作用.结果 甲杓肌位于喉腔内,环杓后肌、环杓侧肌、杓横肌及杓斜肌位于喉软骨支架的后外周面;在相关肌肉的作用下,以环杓关节面为核心,杓状软骨可以完成旋转与滑动运动;环杓后肌与环杓侧肌可以开大、缩小声门,对保证正常的喉功能有更重要的作用;喉返神经于气管食管沟内自下而上支配环杓后肌、环杓侧肌、杓横机、杓斜肌及甲杓肌等肌肉;喉下动脉自甲状腺下动脉发出后走行于环杓后肌的背侧,供血于环杓关节相关组织.结论 一侧完整的环杓关节及功能正常的环杓后肌与环杓侧肌是保留喉功能喉部分切除术的最基本条件.