Prevalence effects in visual search: Theoretical and practical implications

描述（由申请人提供）：考虑通过骨骼扫描或CT来确定患者是否对癌症治疗有反应。或者，作为一个不那么生死攸关的案例，考虑在一个孩子的玩具盒里寻找所有可以用来建造屋顶的乐高积木。这是对多种目标类型的多个实例的复杂、扩展的视觉搜索，无论是癌症转移还是特定形状的构建块。人类如何执行这些任务？我们如何帮助专家更有效地执行我们的文明在诊所、机场和其他地方创造的关键扩展搜索任务？在过去的25年里，人们对视觉选择性注意的基本过程的理解取得了很大的进展。也就是说，现有的大部分工作都是针对单一类别目标的单个实例进行简短的搜索（秒）（例如，找到一条红色垂直线或这个特定对象）。通常，该目标将出现在50%或更多的试验中。为了理解和改进放射学和其他领域的重要搜索任务，我们必须研究扩展的视觉搜索任务。提出的工作利用三个扩展的搜索范式，很大程度上是新的研究人类搜索。觅食任务类似于在田野里采摘浆果或胸部CT上的肺结节。观察者试图在固定的时间内选择尽可能多的目标物品。为了模拟这种行为，导引搜索（GS）模型从动物觅食、决策理论和神经经济学的文献中得到了扩充。混合搜索任务包括搜索几种可能类型的目标中的任何一种的视觉显示（想想购物清单或疾病迹象清单）。这是视觉搜索和记忆搜索的结合。在内存中搜索数百个不同的对象是可能的。为了模拟这种行为，从工作记忆和长期记忆（LTM）研究的想法被引入到GS框架。最后，混合觅食任务结合了觅食任务和混合任务的需求。在这里，观察者试图收集尽可能多的多种类型的目标的例子。我们在与非专家观察员的实验室研究和与专家放射科医生的实验中使用这些方法。我们试图描述和模拟扩展搜索的基本过程，并提高放射科医生和其他专家执行此类搜索的能力。特别令人感兴趣的是寻找罕见的、低患病率的目标（例如，乳腺癌筛查人群中的癌症出现在约0.3%的检查中）。在临床环境中，假阴性、漏诊的发生率较低。建议的工作提出了改善这种影响的技术，并检查了在扩展搜索任务中流行的影响。总之，这项工作开发了一个跨学科的GS扩展，应用于扩展的搜索任务，其最终目标是提高在放射学和其他社会重要环境中发现的关键搜索任务的性能。

DESCRIPTION (provided by applicant): Consider looking at a bone scan or a CT to determine if a patient is responding to cancer treatment. Or, as a less life-and-death case, consider searching through a child's toy box for all the Lego pieces that can be used to build a roof on today's project. These are complex, extended visual searches for multiple instances of multiple target types, be they metastases of cancer or building blocks of a particular shape. How do humans perform such tasks and how can we help experts to perform more effectively the critical extended search tasks that our civilization has created in the clinic, the airport, and elsewhere? The past 25+ years have seen great progress in understanding the basic process of visual selective attention. That said, the bulk of the existing work involves brief episodes of search (seconds) for a single instance of a single class of target (e.g. find a red vertical line or this specific object). Typically, that target will be present on 50% or more of trials. In order to understand and improve upon socially important search tasks in radiology and elsewhere, we must investigate extended visual search tasks. The proposed work exploits three extended search paradigms, largely new to the study of human search. Foraging tasks are laboratory analogs of picking berries in a field or lung nodules in a chest CT. Observers try to select as many target items as possible in a fixed period of time. To model this behavior, the Guided Search (GS) model is augmented with ideas from the literature on animal foraging as well as decision theory and neuroeconomics. Hybrid Search tasks involve searching visual displays for any of several possible types of target (think of a shopping list or a checklist of signs of disease). These are combinations of visual search and memory search. It is possible to search for literally hundreds of distinct objects, held in memory. To model this behavior, ideas from the study of working memory and long-term memory (LTM) are brought into the GS framework. Finally, Hybrid Foraging tasks combine the demands of the foraging and hybrid tasks. Here, observers attempt to collect as many examples as possible of multiple types of targets. We use each of these methods in laboratory studies with non-expert observers and in experiments with expert radiologists. We seek to describe and model the fundamental processes of extended search and to improve the ability of radiologists and other experts to perform such searches. Of particular interest are searches for rare, low prevalence targets (e.g. cancer in a breast cancer screening population appears in about 0.3% of exams). False negative, miss errors are elevated at low prevalence in clinical settings. The proposed work suggests techniques for ameliorating this effect and examines the impact of prevalence in extended search tasks. In summary, this work develops an interdisciplinary extension of GS, applied to extended search tasks, with the ultimate goal of improving performance on the critical search tasks found in radiology and other socially important settings.