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IMPORTANCE A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.OBJECTIVE To establish a DLS for detection of GON using retinal fundus images and glaucoma diagnosis with convoluted neural networks (GD-CNN) that has the ability to be generalized across populations. DESIGN, SETTING, AND PARTICIPANTSIn this cross-sectional study, a DLS for the classification of GON was developed for automated classification of GON using retinal fundus images obtained from the Chinese Glaucoma Study Alliance, the Handan Eye Study, and online databases. The researchers selected 241 032 images were selected as the training data set. The images were entered into the databases on June 9, 2009, obtained on July 11, 2018, and analyses were performed on December 15, 2018. The generalization of the DLS was tested in several validation data sets, which allowed assessment of the DLS in a clinical setting without exclusions, testing against variable image quality based on fundus photographs obtained from websites, evaluation in a population-based study that reflects a natural distribution of patients with glaucoma within the cohort and an additive data set that has a diverse ethnic distribution. An online learning system was established to transfer the trained and validated DLS to generalize the results with fundus images from new sources. To better understand the DLS decision-making process, a prediction visualization test was performed that identified regions of the fundus images utilized by the DLS for diagnosis. EXPOSURES Use of a deep learning system. MAIN OUTCOMES AND MEASURES Area under the receiver operating characteristics curve (AUC), sensitivity and specificity for DLS with reference to professional graders. RESULTS From a total of 274 413 fundus images initially obtained from CGSA, 269 601 images passed initial image quality review and were graded for GON. A total of 241 032 images (definite GON 29 865 [12.4%], probable GON 11 046 [4.6%], unlikely GON 200 121 [83%]) from 68 013 patients were selected using random sampling to train the GD-CNN model. Validation and evaluation of the GD-CNN model was assessed using the remaining 28 569 images from CGSA. The AUC of the GD-CNN model in primary local validation data sets was 0.996 (95% CI, 0.995-0.998), with sensitivity of 96.2% and specificity of 97.7%. The most common reason for both false-negative and false-positive grading by GD-CNN (51 of 119 [46.3%] and 191 of 588 [32.3%]) and manual grading (50 of 113 [44.2%] and 183 of 538 [34.0%]) was pathologic or high myopia.CONCLUSIONS AND RELEVANCE Application of GD-CNN to fundus images from different settings and varying image quality demonstrated a high sensitivity, specificity, and generalizability for detecting GON. These findings suggest that automated DLS could enhance current screening programs in a cost-effective and time-efficient manner.

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The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

From its outset, the concept of social representations has been utilised in many different ways both in theoretical articulations and in empirical studies. What is commonly accepted for both the pros and cons of the theory of social representations is that there is no commonly accepted definition of the concept. Undoubtedly, the theory has gained its currency due to its critical and innovative contributions to social psychology. The current status of the concept, however, provokes some unfavourable propositions to the theory. Some, for instance Dittmar (1992), try to incorporate the theory into the umbrella of social constructionism. Others, for instance Potter and Edwards (1999), argue for refuting the theory. These misleading voices to the theory imply that some epistemological aspects of the concept of social representations remain unsolved.This article aims at clarifying some critical, but under-explored, conceptual issues in the theory of social representations from a dialogical perspective. The article consists of five distinct, but interrelated, parts. In response to the criticism of the concept as "vague" or "ill-defined", Part I argues that social representations are dialogical, but not monological, phenomena; the notion of social representations is thus a sensitising, rather than a definitive, concept. Part II argues that the concept of themata is theoretically more appropriate than the core-peripheral approach in capturing the origin, structure and dynamics of social representations. Part III argues that the transformation from themata to their pragmatic manifestations is a dynamic and continually evolving process which is dependent upon both anchoring and objectification. Part IV presents partial findings from my own empirical study of quality of life as a social representation in China. These findings illustrate and support the theoretical arguments on the dialogical interdependence between common thinking and social morphology, between the genesis and structure of social representations, and between implicit underlying themata and their pragmatic manifestations. Part V suggests that, in the light of the concept of themata, a social representation may be, at one and the same time,

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The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

China's rural-urban dual society system is instituted by its unique hukou system. This system causes inequalities in social status between permanent urban and rural residents, and discrimination against rural-to-urban migrants is thus prevalent. A series of studies, based on system justification theory, sought to address the impact of the hukou system on the discrimination against rural-to-urban migrants. Study 1 showed that the justification of the hukou system could predict discrimination operationalized using a social distance measure. Study 2 found that priming of the proposed abolishment of the current hukou system led to reduced social distance. Study 3, using a recruiting scenario, further demonstrated that priming of the proposed abolishment of the system led to reduced discrimination in salary decision. Consistent with our predictions, discrimination against rural-to-urban migrants could be triggered by justifying the current hukou system, while priming of the abolishment of the system serves to decrease discrimination. The present research thereby sheds light on China's reform of its hukou system to achieve social justice and equality from a psychological perspective.