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Abstract Antenatal hydronephrosis (HN) impacts up to 5% of pregnancies and requires close, frequent follow-up monitoring to determine who may benefit from surgical intervention. To create an automated HN Severity Index (HSI) that helps guide clinical decision-making directly from renal ultrasound images. We applied a deep learning model to paediatric renal ultrasound images to predict the need for surgical intervention based on the HSI. The model was developed and studied at four large quaternary free-standing paediatric hospitals in North America. We evaluated the degree to which HSI corresponded with surgical intervention at each hospital using area under the receiver-operator curve, area under the precision-recall curve, sensitivity, and specificity. HSI predicted subsequent surgical intervention with > 90% AUROC, > 90% sensitivity, and > 70% specificity in a test set of 202 patients from the same institution. At three external institutions, HSI corresponded with AUROCs ≥ 90%, sensitivities ≥ 80%, and specificities > 50%. It is possible to automatically and reliably assess HN severity directly from a single ultrasound. The HSI stratifies low- and high-risk HN patients thus helping to triage low-risk patients while maintaining very high sensitivity to surgical cases. HN severity can be predicted from a single patient ultrasound using a novel image-based artificial intelligence system.

Physicists, physics students, and community members come together and engage with physics content through various forms of informal education programming. Our prior work has shown that the landscape of informal physics programs in the United States has a variety of formats, audience demographics, and content. Informal physics programs have many benefits for both facilitators and community members; however, we do not fully understand how the variety of program structures, designs, and organizations affect participants' experiences. In this study, we apply an organizational theory framework to study the connectedness of six functional aspects of informal physics programs: "Assessment," "Audience," "Institution," "Personnel," "Program," and "Resources." We interview lead facilitators about the design and structure of their programs. Here we present an in-depth qualitative analysis of three cases. We find that the personnel, consisting of the faculty, staff, and physics students facilitating the educational activities, have a prominent role in these programs. Our findings show how personnel members influence the physics content, activities, and interactions with the audience. We discuss how understanding these aspects can help support improving the functionality of informal physics programs in equitable and inclusive ways.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.