Chest imaging plays a pivotal role in screening and monitoring patients, and various predictive artificial intelligence (AI) models have been developed in support of this. However, little is known about the effect of decreasing the radiation dose and, thus, image quality on AI performance. This study aims to design a low-dose simulation and evaluate the effect of this simulation on the performance of CNNs in plain chest radiography. Seven pathology labels and corresponding images from Medical Information Mart for Intensive Care datasets were used to train AI models at two spatial resolutions. These 14 models were tested using the original images, 50% and 75% low-dose simulations. We compared the area under the receiver operator characteristic (AUROC) of the original images and both simulations using DeLong testing. The average absolute change in AUROC related to simulated dose reduction for both resolutions was <0.005, and none exceeded a change of 0.014. Of the 28 test sets, 6 were significantly different. An assessment of predictions, performed through the splitting of the data by gender and patient positioning, showed a similar trend. The effect of simulated dose reductions on CNN performance, although significant in 6 of 28 cases, has minimal clinical impact. The effect of patient positioning exceeds that of dose reduction.
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This study explores the shape-morphing behavior of 4D-printed structures made from Polylactic Acid (PLA), a prominent bio-sourced shape-memory polymer. Focusing on the response of these structures to thermal stimuli, this research investigates how various printing parameters influence their morphing capabilities. The experimental approach integrates design and slicing, printing using fused deposition modeling (FDM), and a post-printing activation phase in a controlled laboratory environment. This process aims to replicate the external stimuli that induce shape morphing, highlighting the dynamic potential of 4D printing. Utilizing Taguchi’s Design of Experiments (DoE), this study examines the effects of printing speed, layer height, layer width, nozzle temperature, bed temperature, and activation temperature on the morphing behavior. The analysis includes precise measurements of deformation parameters, providing a comprehensive understanding of the morphing process. Regression models demonstrate strong correlations with observed data, suggesting their effectiveness in predicting responses based on control parameters. Additionally, finite element analysis (FEA) modeling successfully predicts the performance of these structures, validating its application as a design tool in 4D printing. This research contributes to the understanding of 4D printing dynamics and offers insights for optimizing printing processes to harness the full potential of shape-morphing materials. It sets a foundation for future research, particularly in exploring the relationship between printing parameters and the functional capabilities of 4D-printed structures.
For decades, Scandinavian culture effectively prohibited the development of special provisions for talented students in higher education. However, in recent years, a cultural shift has gradually made more room for excellence and talent development in the national discourses. This paper analyzes the climate for talent development in Denmark, Sweden, and Norway. Following a first inventory of honors programs in Scandinavian higher education in which the only programs were found in Denmark, 10 experts were interviewed to analyze their national situation and reflect on the leading role of Denmark. In this country, external incentives, focus on quality, pioneers, and an open atmosphere were found to produce a culture more appreciative of excellence over the last decade. Starting from the Danish experience, the situation in Norway and Sweden is analyzed, showing that the combination of factors leading to change in Denmark is not yet present here. Lessons for other countries are highlighted, notably the importance of sharing information and exchanging knowledge at an international level.
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