Publications by authors named "J Y Brown"

Large Language Models (LLMs) such as ChatGPT have been increasingly integrated into radiology research, revolutionizing the research landscape. The Radiology Research Alliance (RRA) of the Association for Academic Radiology (AAR) has convened a Task Force to develop this guide to help radiology researchers responsibly adopt LLM technologies. LLMs can improve various phases of the research process by helping to automate literature reviews, generate research questions, analyze complex datasets, and draft manuscripts.

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Purpose: Sharing aggregate results with research participants is a widely agreed-upon ethical obligation; yet, there is little research on communicating study results to diverse populations enrolled in genomics research. This article describes the cocreation of a visual narrative to explain research findings to families enrolled in a clinical genomics research study.

Methods: The design process involved researchers, clinicians, study participants, a physician illustrator, and a health communications expert.

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While the genetic paradigm of cancer etiology has proven powerful, it remains incomplete as evidenced by the widening spectrum of non-cancer cell-autonomous "hallmarks" of cancer. Studies have demonstrated the commonplace presence of high oncogenic mutational burdens in homeostatically-stable epithelia. Hence, the presence of driver mutations alone does not result in cancer.

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The relationship between left atrial enlargement (LAE) and primary cryptogenic stroke (PCS) remains a mystery. LAE has been proposed to be an independent risk factor of PCS, recurrent ischemic strokes, paroxysmal atrial fibrillation, and thromboembolism. Our study evaluates the prevalence of LAE among patients with PCS in the absence of atrial fibrillation, unlike previous studies that included atrial fibrillation, in order to isolate LAE as a risk factor.

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