Perceptual and Adaptive Learning in Cancer Image Interpretation

项目摘要/摘要 从视觉显示器上进行癌症筛查，就像皮肤科和放射科一样，关键取决于 医生，但目前的数据表明，即使在经验丰富的专业人士中，也有显著的 和持久的错误率。虽然医学成像技术取得了令人印象深刻的进步， 对医学图像训练中涉及的学习过程的关注要少得多 释义。对感知和认知的研究表明，人们成为 能够检测和分类视觉图像中的复杂和细微的模式和结构的过程称为 知觉学习。通过知觉学习机制，在特定领域进行适当的练习， 大脑逐步改进信息提取，以优化任务绩效。这些机制是 基本不受医学教育中常见的传统说教的影响；相反，他们依赖于 通过与任务相关的反馈，与大量的例子互动。最近的研究表明， 应用知觉学习原理可以显著提高医学诊断的准确性和流畅性 学习领域。有证据表明，这些培训方法可以显著增强，并进行定制 对于个体学习者，通过结合基于学习原理的新的自适应学习算法和 记忆。 本项目的主要目的是研究知觉学习和适应性学习的原理和机制。 在学习皮肤病筛查和乳房X光检查中的多种诊断类别时， 最终目标是提高癌症图像判读的培训和熟练程度。与实验室中的新手进行研究 设置将建立基本原则和假设，并与护士黑素摄影者进行选择性研究， 住院医生和医生将与实际医生一起测试验证。对黑素摄影家的研究达到高潮 实际的皮肤病筛查设置将比较接受过最佳实践培训的从业者 用于控制参与者的自适应学习模块(Palms)。具体的研究将调查合并 自适应感知学习系统中的信号检测概念；比较在定义和 区分感知类别；被动和主动学习事件的相对好处 学习阶段；以及掌握标准的严格程度与以下程度之间的关系 最终的表现是准确、流畅、可概括和持久的。

Project Summary/Abstract Cancer screening from visual displays, as in dermatology and radiology, depends crucially on the expertise of medical practitioners, but current data indicate that even among experienced professionals there are significant and persistent error rates. While there have been impressive advances in the technologies of medical imaging, considerably less attention has been paid to the learning processes involved in the training of medical image interpretation. Research in perception and cognition indicates that the central process by which people become able to detect and classify complex and subtle patterns and structures in visual images is a process known as perceptual learning. Through perceptual learning mechanisms, with appropriate practice in a given domain, the brain progressively improves information extraction to optimize task performance. These mechanisms are largely unaffected by the traditional didactic instruction common in medical education; instead, they depend on interaction with large numbers of examples with task-relevant feedback. Recent work has shown that application of principles of perceptual learning can dramatically accelerate accuracy and fluency in medical learning domains. Evidence suggests that these training methods can be markedly enhanced, and customized for individual learners, by incorporating novel adaptive learning algorithms based on principles of learning and memory. The primary aim of this project is to investigate principles and mechanisms of perceptual and adaptive learning in the learning of multiple diagnostic categories in dermatologic screening and mammography, with the ultimate aim of improving training and proficiency in cancer image interpretation. Studies with novices in lab settings will establish basic principles and hypotheses, and selective studies with nurse melanographers, residents, and physicians will test validation with actual practitioners. Culminating studies of melanographers in actual dermatologic screening settings will compare practitioners who train with best-practices perceptual- adaptive learning modules (PALMs) to control participants. Specific studies will investigate the incorporation of signal detection concepts into adaptive perceptual learning systems; the role of comparisons in defining and differentiating perceptual categories; the relative benefits of passive and active learning episodes across learning phases; and the relationship between the stringency of mastery criteria and the degree to which resulting performance is accurate, fluent, generalizable, and long-lasting.