Serial Dependence in Radiologist Perception across Naturalistic Mammogram Stimuli

Ren, Zhihang; Cañas-Bajo, Teresa; Zhou, Min; Yu, Stella X.; Whitney, David

doi:10.1167/jov.22.14.3835

Cited by 1 publication

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By subtracting out this future bias, we isolated the 1-trial back effect. This approach-measuring and controlling artifacts by using the future-is a common control in studies of serial dependence [6,8,30,31]. Finally, in a third control, we created permuted and shuffled null distributions.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have tried to measure criterion and d in dermatological judgments over time [36][37][38], but they did not examine trial-wise effects. Serial dependence is a trialby-trial effect [1,2,6,8]: sometimes it happens in random sequences (when sequential stimuli are coincidentally similar) and sometimes it does not happen (when sequential stimuli happen to be different). In typical vision science experiments, stimuli are random and their sequential similarity is not measured, considered, or controlled.…”

Section: Discussionmentioning

confidence: 99%

“…However, these studies were conducted under lab conditions with highly artificial stimuli and experimental designs that are not typical in clinical practice [6]. More recently, progress in Generative Adversarial Networks (GANs) affords the opportunity to generate more realistic simulated medical images as stimuli [7,8]. However, even in these studies, the relatively complex psychophysical tasks were not comparable to realistic, clinically relevant scenarios.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Serial Dependence in Dermatological Judgments

Ren

Pietralla

et al. 2023

Diagnostics

View full text Add to dashboard Cite

Serial Dependence is a ubiquitous visual phenomenon in which sequentially viewed images appear more similar than they actually are, thus facilitating an efficient and stable perceptual experience in human observers. Although serial dependence is adaptive and beneficial in the naturally autocorrelated visual world, a smoothing perceptual experience, it might turn maladaptive in artificial circumstances, such as medical image perception tasks, where visual stimuli are randomly sequenced. Here, we analyzed 758,139 skin cancer diagnostic records from an online app, and we quantified the semantic similarity between sequential dermatology images using a computer vision model as well as human raters. We then tested whether serial dependence in perception occurs in dermatological judgments as a function of image similarity. We found significant serial dependence in perceptual discrimination judgments of lesion malignancy. Moreover, the serial dependence was tuned to the similarity in the images, and it decayed over time. The results indicate that relatively realistic store-and-forward dermatology judgments may be biased by serial dependence. These findings help in understanding one potential source of systematic bias and errors in medical image perception tasks and hint at useful approaches that could alleviate the errors due to serial dependence.

show abstract

Section: Discussionmentioning

confidence: 99%