527,203 research outputs found

    A Field Test of Popular Chatbots’ Responses To Questions Concerning Negative Body Image

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    Background: Chatbots are computer programs, often built upon large artificial intelligence models, that employ dialogue systems to enable online, natural language conversations with users via text, speech, or both. Body image, broadly defined as a combination of thoughts and feelings about one’s physical appearance, has been implicated in many risk behaviors and health problems, especially among adolescents and young adults. Little is known about how chatbots respond to questions about body image. Methods: This study assessed the responses of 14 widely-used chatbots (eight companion and six therapeutic chatbots) to ten body image-related questions developed upon validated instruments. Chatbots’ responses were documented, with qualities systematically assessed by nine pre-determined criteria. Results: The overall quality of the chatbots’ responses was modest (an average score of five out of nine), with substantial variations in the content and quality of responses across chatbots (individual scores ranging from one to eight). Companion and therapeutic chatbots systematically differed in their responses (e.g., focusing on comforting users vs. trying to identify the causes of negative body image and recommending potential remedies). Some therapeutic chatbots recognized potential mental health crises (self-harm) in test users’ messages. Conclusion: Substantial heterogeneities in the responses were present across chatbots and assessment criteria. Adolescents and young adults struggling with body image could be vulnerable to misleading or biased remarks made by chatbots. Still, the technical and supervision challenges to prevent those adverse consequences remain paramount and unsolved

    Optimisation of the digital radiographic imaging of suspected non-accidental injury.

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    Aim: To optimise the digital (radiographic) imaging of children presenting with suspected non-accidental injury (NAI).;Objectives: (i) To evaluate existing radiographic quality criteria, and to develop a more suitable system if these are found to be inapplicable to skeletal surveys obtained in suspected NAI. (ii) To document differences in image quality between conventional film-screen and the recently installed Fuji5000R computed radiography (CR) system at Great Ormond Street Hospital for Children, (iii) To document the extent of variability in the standard of skeletal surveys obtained in the UK for suspected NAI. (iv) To determine those radiographic parameters which yield the highest diagnostic accuracy, while still maintaining acceptable radiation dose to the child, (v) To determine how varying degrees of edge-enhancement affect diagnostic accuracy. (vi) To establish the accuracy of soft compared to hard copy interpretation of images in suspected NAI.;Materials and Methods: (i) and (ii) Retrospective analysis of 286 paediatric lateral spine radiographs by two observers based on the Commission of European Communities (CEC) quality criteria, (iii) Review of the skeletal surveys of 50 consecutive infants referred from hospitals throughout the United Kingdom (UK) with suspected NAI. (iv) Phantom studies. Leeds TO. 10 and TO. 16 test objects were used to compare the relationship between film density, exposure parameters and visualisation of object details, (iv) Clinical study. Anteroposterior and lateral post mortem skull radiographs of six consecutive infants were obtained at various exposures. Six observers independently scored the images based on visualisation of five criteria, (v) and (vi) A study of diagnostic accuracy in which six observers independently interpreted 50 radiographs from printed copies (with varying degrees of edge-enhancement) and from a monitor.;Results: The CEC criteria are useful for optimisation of imaging parameters and allow the detection of differences in quality of film-screen and digital images. There is much variability in the quality and number of radiographs performed as part of skeletal surveys in the UK for suspected NAI. The Leeds test objects are either not sensitive enough (TO. 10) or perhaps over sensitive (TO. 16) for the purposes of this project. Furthermore, the minimum spatial resolution required for digital imaging in NAI has not been established. Therefore the objective interpretation of phantom studies is difficult. There is scope for reduction of radiation dose to children with no effect on image quality. Diagnostic accuracy (fracture detection) in suspected NAI is generally low, and is not affected by image display modality.;Conclusions: The CEC quality criteria are not applicable to the assessment of clinical image quality. A national protocol for skeletal surveys in NAI is required. Dedicated training, close supervision, collaboration and consistent exposure of radiologists to cases of NAI should improve diagnostic accuracy. The potential exists for dose reduction when performing skeletal surveys in children and infants with suspected NAI. Future studies should address this issue

    A statistical reduced-reference method for color image quality assessment

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    Although color is a fundamental feature of human visual perception, it has been largely unexplored in the reduced-reference (RR) image quality assessment (IQA) schemes. In this paper, we propose a natural scene statistic (NSS) method, which efficiently uses this information. It is based on the statistical deviation between the steerable pyramid coefficients of the reference color image and the degraded one. We propose and analyze the multivariate generalized Gaussian distribution (MGGD) to model the underlying statistics. In order to quantify the degradation, we develop and evaluate two measures based respectively on the Geodesic distance between two MGGDs and on the closed-form of the Kullback Leibler divergence. We performed an extensive evaluation of both metrics in various color spaces (RGB, HSV, CIELAB and YCrCb) using the TID 2008 benchmark and the FRTV Phase I validation process. Experimental results demonstrate the effectiveness of the proposed framework to achieve a good consistency with human visual perception. Furthermore, the best configuration is obtained with CIELAB color space associated to KLD deviation measure

    Influence of study design on digital pathology image quality evaluation : the need to define a clinical task

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    Despite the current rapid advance in technologies for whole slide imaging, there is still no scientific consensus on the recommended methodology for image quality assessment of digital pathology slides. For medical images in general, it has been recommended to assess image quality in terms of doctors’ success rates in performing a specific clinical task while using the images (clinical image quality, cIQ). However, digital pathology is a new modality, and already identifying the appropriate task is difficult. In an alternative common approach, humans are asked to do a simpler task such as rating overall image quality (perceived image quality, pIQ), but that involves the risk of nonclinically relevant findings due to an unknown relationship between the pIQ and cIQ. In this study, we explored three different experimental protocols: (1) conducting a clinical task (detecting inclusion bodies), (2) rating image similarity and preference, and (3) rating the overall image quality. Additionally, within protocol 1, overall quality ratings were also collected (task-aware pIQ). The experiments were done by diagnostic veterinary pathologists in the context of evaluating the quality of hematoxylin and eosin-stained digital pathology slides of animal tissue samples under several common image alterations: additive noise, blurring, change in gamma, change in color saturation, and JPG compression. While the size of our experiments was small and prevents drawing strong conclusions, the results suggest the need to define a clinical task. Importantly, the pIQ data collected under protocols 2 and 3 did not always rank the image alterations the same as their cIQ from protocol 1, warning against using conventional pIQ to predict cIQ. At the same time, there was a correlation between the cIQ and task-aware pIQ ratings from protocol 1, suggesting that the clinical experiment context (set by specifying the clinical task) may affect human visual attention and bring focus to their criteria of image quality. Further research is needed to assess whether and for which purposes (e.g., preclinical testing) task-aware pIQ ratings could substitute cIQ for a given clinical task
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