论文标题

打开视觉探索视觉探索的视听数字生物标志物:OPENDBM分析工具

Opening Access to Visual Exploration of Audiovisual Digital Biomarkers: an OpenDBM Analytics Tool

论文作者

Floricel, Carla, Epifano, Jacob, Caamano, Stephanie, Kark, Sarah, Christie, Rich, Masino, Aaron, Paredes, Andre D

论文摘要

数字生物标志物(DBM)是一个不断增长的领域,在精神病和神经退行性疾病的治疗领域进行了越来越多的测试。同时,在工业,学术界和诊所中使用的视听DBM的知识孤立的孤立孤岛阻碍了它们在临床研究中的广泛采用。我们如何帮助这些非技术领域专家探索视听数字生物标志物?在生物医学研究中使用开源软件来提取患者行为的变化正在增长,并激发了向解决此问题的可访问性转变。 OPENDBM集成了几个流行的音频和视觉开源行为提取工具包。我们提出了一个视觉分析工具,作为不断增长的开源软件OpenDBM的扩展,以促进基本和应用研究中的视听DBM。我们的工具说明了行为数据中的模式,同时支持通过OPENDBM提取的任何派生或原始DBM变量的任何子集的交互式视觉分析。

Digital biomarkers (DBMs) are a growing field and increasingly tested in the therapeutic areas of psychiatric and neurodegenerative disorders. Meanwhile, isolated silos of knowledge of audiovisual DBMs use in industry, academia, and clinics hinder their widespread adoption in clinical research. How can we help these non-technical domain experts to explore audiovisual digital biomarkers? The use of open source software in biomedical research to extract patient behavior changes is growing and inspiring a shift toward accessibility to address this problem. OpenDBM integrates several popular audio and visual open source behavior extraction toolkits. We present a visual analysis tool as an extension of the growing open source software, OpenDBM, to promote the adoption of audiovisual DBMs in basic and applied research. Our tool illustrates patterns in behavioral data while supporting interactive visual analysis of any subset of derived or raw DBM variables extracted through OpenDBM.

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