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What have we learned about prevalence in visual search and can we apply our findings to medical image perception?

机译:我们从视觉搜索的流行中学到了什么,可以将我们的发现应用于医学图像感知吗?

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Interpretation of medical images is a socially critical application of visual search. The prevalence of targets in medical image search tasks varies widely. While a screening mammographer will see one cancer for every 300 cases, a pathologist interpreting biopsies will see mostly positive cases. How does prevalence affect visual search? Do low and high prevalence exert similar effects? Can findings from the basic vision science literature be generalized to the medical image perception context? I have previously reported a meta-analysis results show that basic cognitive psychology and applied medical image perception studies converge on an account of the low prevalence effect: sensitivity (d') is constant with prevalence, but criterion (c) shifts to a more conservative level at low prevalence (Horowitz, 2017). Here I show that these results generalize to the high prevalence effect: sensitivity does not change at high prevalence, but criterion shifts to a more liberal level. I synthesize findings from both vision science and medical image perception, I will identify practical suggestions for medical image professionals and theoretical insights for vision scientists.
机译:医学图像的解释是视觉搜索的社会关键应用。在医学图像搜索任务中目标的普遍程度差异很大。筛查的乳房X光检查人员每300例中会发现一种癌症,而解释活组织检查的病理学家将主要看到阳性病例。患病率如何影响视觉搜索?低流行率和高流行率会产生相似的影响吗?基本视觉科学文献的发现是否可以推广到医学图像感知环境?我以前曾报道过一项荟萃分析的结果表明,基本的认知心理学和应用的医学图像感知研究基于较低的患病率效应而趋于一致:灵敏度(d')与患病率一致,但标准(c)转向较为保守患病率低(Horowitz,2017)。在这里,我表明这些结果可以概括为较高的患病率效果:敏感性在较高的患病率中不会改变,但标准会转移到更自由的水平。我综合了视觉科学和医学图像感知的发现,我将为医学图像专业人员确定实用建议,并为视觉科学家提供理论见解。

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