UNASSIGNED: Chest X-rays (CXR) are widely used to facilitate the diagnosis and treatment of critically ill and emergency patients in clinical practice. Accurate hemi-diaphragm detection based on postero-anterior (P-A) CXR images is crucial for the diaphragm function assessment of critically ill and emergency patients to provide precision healthcare for these vulnerable populations.
UNASSIGNED: Therefore, an effective and accurate hemi-diaphragm detection method for P-A CXR images is urgently developed to assess these vulnerable populations\' diaphragm function.
UNASSIGNED: Based on the above, this paper proposes an effective hemi-diaphragm detection method for P-A CXR images based on the convolutional neural network (CNN) and graphics. First, we develop a robust and standard CNN model of pathological lungs trained by human P-A CXR images of normal and abnormal cases with multiple lung diseases to extract lung fields from P-A CXR images. Second, we propose a novel localization method of the cardiophrenic angle based on the two-dimensional projection morphology of the left and right lungs by graphics for detecting the hemi-diaphragm.
UNASSIGNED: The mean errors of the four key hemi-diaphragm points in the lung field mask images abstracted from static P-A CXR images based on five different segmentation models are 9.05, 7.19, 7.92, 7.27, and 6.73 pixels, respectively. Besides, the results also show that the mean errors of these four key hemi-diaphragm points in the lung field mask images abstracted from dynamic P-A CXR images based on these segmentation models are 5.50, 7.07, 4.43, 4.74, and 6.24 pixels,respectively.
UNASSIGNED: Our proposed hemi-diaphragm detection method can effectively perform hemi-diaphragm detection and may become an effective tool to assess these vulnerable populations\' diaphragm function for precision healthcare.

OBJECTIVE: We sought to analyze interactive visualizations and animations of health probability data (such as chances of disease or side effects) that have been studied in head-to-head comparisons with either static graphics or numerical communications.
METHODS: Secondary analysis of a large systematic review on ways to communicate numbers in health.
RESULTS: We group the research to show that 4 types of animated or interactive visualizations have been studied by multiple researchers: those that simulate experience of probabilistic events; those that demonstrate the randomness of those events; those that reduce information overload by directing attention sequentially to different items of information; and those that promote elaborative thinking. Overall, these 4 types of visualizations do not show strong evidence of improving comprehension, risk perception, or health behaviors over static graphics.
CONCLUSIONS: Evidence is not yet strong that interactivity or animation is more effective than static graphics for communicating probabilities in health. We discuss 2 possibilities: that the most effective visualizations haven\'t been studied, and that the visualizations aren\'t effective.
CONCLUSIONS: Future studies should rigorously compare participant performance with novel interactive or animated visualizations against their performance with static visualizations. Such evidence would help determine whether health communicators should emphasize novel interactive visualizations or rely on older forms of visual communication, which may be accessible to broader audiences, including those with limited digital access.

Investigations of stereoscopic depth perception were transformed via the use of computer-generated random-dot stereograms in the 1960s. They realized Wheatstone\'s wish of demonstrating binocular depth without monocular object recognition, and they have been the dominant stimulus for studying stereopsis since then. Alternative carrier patterns to random dots, based on graphics, photographs, and their combinations, are presented as anaglyphs and for free fusion. A wider range of concealed patterns can be revealed with these alternatives, and presenting them as anaglyphs can yield patterns that have visual appeal independent of the depth they conceal.

A graphical abstract (GA) summarizes the key and important findings of an article graphically, potentially stimulating researchers to view the published manuscript. A GA should enhance dissemination, augment engagement, and impact clinical practice. Infographics play a key role in a quicker understanding of the significant findings of a manuscript. Few level 1 studies reported that GAs enhanced the engagement of readers on social media when compared to plain text abstracts. With the evolution of Industry 4.0, 5.0, and 6.0, GA plays a major role in understanding the technical aspects of various technologies. This article outlines tips to prepare an effective GA and reports the impact of GAs on research and clinical translation.

OBJECTIVE: This study aimed to analyze and quantify the representation of dark skin tones (DST) images/graphics across fifteen foundational and clinical nursing textbooks to understand the degree of portrayed diversity in current nursing texts.
BACKGROUND: The United States (U.S.) population is becoming more ethnically and racially diverse. There is a scarcity of nursing literature, studies, and educational materials on the assessment and early recognition of common skin assessment in patients with dark skin tones (DST). The underrepresentation of people with DST images in didactic material suggests that omissions of these images in educational resources may introduce bias in health care provider education and practice.
METHODS: Fifteen popular foundational and clinical nursing textbooks were selected and analyzed. All the photo images and drawn graphics in these textbooks were coded according to Fitzpatrick\'s skin phototype (FSP) scale, which categorizes skin tone as (a) \"Light\" or Fitzpatrick scale I or II, (b) \"Medium\" or Fitzpatrick scale III or IV, and (c) \"Dark\" or Fitzpatrick scale V or VI. The training was provided for data collectors before analysis to ascertain good inter-rater reliability (Cohen\'s kappa = 0.960 for light skin tone, Cohen\'s kappa = 0.899 for medium skin tone, and Cohen\'s kappa = 0.913 for dark skin tone).
RESULTS: Analysis of 14,192 photo images and drawn graphics depicting skin tone was completed across 15 foundational and clinical nursing textbooks. 12.3 % of photo images and 2.4 % of drawn graphics depicted dark skin tones, compared to 60.9 % of photo images and 82.8 % of drawn graphics that displayed light skin tones in these textbooks.
CONCLUSIONS: Nursing textbooks overrepresent light skin tones and underrepresent dark skin tones. While the approximate racial distribution of the U.S. population is 59.3 % non-Hispanic-White, 13.6 % Black/African American, and 26.6 % Person of Color, the images and graphics of skin tones represented 68 % light, 15 % medium, and 9.4 % dark.
CONCLUSIONS: All healthcare providers are expected and required to deliver competent clinical care to an increasingly diverse population. For teaching-learning, more visual representations of DST and comparative images between what to expect in dark, medium, and light skin tones can help improve knowledge deficits and increase health equity.

This paper presents a novel architecture to generate a world model in terms of mesh from a continuous image stream with depth information extracted from a robot\'s ego-vision camera. We propose two algorithms for planar and non-planar mesh generation. A Cartesian grid-based mesh fitting algorithm is proposed for mesh generation of planar objects. For mesh generation of non-planar objects, we propose a Self Organization Map based algorithm. The proposed algorithm better approaches the boundary and overall shape of the objects compared to State-Of-the-Art (SOA). Extensive experiments done on three public datasets show that our method surpasses SOA both qualitatively and quantitatively.

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Illustrated review articles, rooted in scientific rigor, are made up of \"capsules\" or panels of visuals that together provide an up-to-date overview of a topic. Illustrated reviews aim to provide a more accessible format than traditional written reviews to facilitate more effective knowledge translation and dissemination. However, the novelty of this format can dissuade prospective authors due to uncertainty and lack of comfort. To remedy this uncertainty, we have summarized the journey of developing an illustrated review, from identifying an appropriate topic to submitting the final manuscript for peer review. We highlight the importance of approaching an illustrated review from a storytelling perspective, and encouraging authors to keep their audience in mind when picking a theme or characters. We provide storyboard considerations and simplify graphic design principles to develop an outline and line draft for the illustrated review. We list programs available to authors to demystify creating attractive and engaging scientific visuals. Finally, we provide information on choosing colors or fonts and where to find copyright-free icons, graphics, illustrations, and pictures. This review provides prospective authors with the knowledge, tools, and resources to create an effective illustrated review article. If there is difficulty with the links embedded within the document please download the full PDF.

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Even though environmental impact assessments (EIAs) have been an important tool for environmental decision-making, most EIAs are published as a mix of text and tabular data that is not easily accessible to or understandable for the public. In this paper, we present a decision support system (DSS) that supports the decision-making of stakeholders in the EIA stage. The system was designed to improve the public\'s understanding of stakeholders before and after a construction project by providing visualization of key environmental elements. We recruited 107 participants to test the usability of the system and examined the impacts of individual differences between the participants on their perceptions of the system, including their environmental expertise and computer self-efficacy. The results showed that the proposed system had high usability, especially for users with high computational efficacy and environment expertise. The system could thus help to improve the communication between the public and experts during public hearings and enhance the environmental literacy of the public.