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Wanyi Lyu; Jennifer S. Trueblood; Jeremy M. Wolfe – Cognitive Research: Principles and Implications, 2025
Low target prevalence affects perceptual decisions on both simple and complex stimuli. Without prior knowledge of how often targets may appear, trial-by-trial accuracy feedback modulates the effects of low prevalence partially by providing observers with information about the target base rate. Using simple colored dots, Lyu (PBR 28:1906-1914,…
Descriptors: Incidence, Feedback (Response), Identification, Cytology
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Francesca Patterson; Melina A. Kunar – Cognitive Research: Principles and Implications, 2024
Computer Aided Detection (CAD) has been used to help readers find cancers in mammograms. Although these automated systems have been shown to help cancer detection when accurate, the presence of CAD also leads to an over-reliance effect where miss errors and false alarms increase when the CAD system fails. Previous research investigated CAD systems…
Descriptors: Cancer, Computer Use, Identification, Screening Tests
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Kunar, Melina A.; Watson, Derrick G. – Cognitive Research: Principles and Implications, 2023
Computer-Aided Detection (CAD) has been proposed to help operators search for cancers in mammograms. Previous studies have found that although accurate CAD leads to an improvement in cancer detection, inaccurate CAD leads to an increase in both missed cancers and false alarms. This is known as the over-reliance effect. We investigated whether…
Descriptors: Assistive Technology, Computer Use, Clinical Diagnosis, Screening Tests
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Kunar, Melina A. – Cognitive Research: Principles and Implications, 2022
People miss a high proportion of targets that only appear rarely. This low prevalence (LP) effect has implications for applied search tasks such as the clinical reading of mammograms. Computer aided detection (CAD) has been used to help radiologists search mammograms by highlighting areas likely to contain a cancer. Previous research has found a…
Descriptors: Incidence, Screening Tests, Cancer, Radiology
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Smithson, Conor J. R.; Eichbaum, Quentin G.; Gauthier, Isabel – Cognitive Research: Principles and Implications, 2023
We investigated the relationship between category learning and domain-general object recognition ability (o). We assessed this relationship in a radiological context, using a category learning test in which participants judged whether white blood cells were cancerous. In study 1, Bayesian evidence negated a relationship between o and category…
Descriptors: Recognition (Psychology), Classification, Learning Processes, Medicine
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Raat, E. M.; Farr, I.; Wolfe, J. M.; Evans, K. K. – Cognitive Research: Principles and Implications, 2021
Expert radiologists can discern normal from abnormal mammograms with above-chance accuracy after brief (e.g. 500 ms) exposure. They can even predict cancer risk viewing currently normal images (priors) from women who will later develop cancer. This involves a rapid, global, non-selective process called "gist extraction". It is not yet…
Descriptors: Cancer, At Risk Persons, Screening Tests, Females
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Raat, E. M.; Kyle-Davidson, C.; Evans, K. K. – Cognitive Research: Principles and Implications, 2023
Extraction of global structural regularities provides general 'gist' of our everyday visual environment as it does the gist of abnormality for medical experts reviewing medical images. We investigated whether naïve observers could learn this gist of medical abnormality. Fifteen participants completed nine adaptive training sessions viewing four…
Descriptors: Feedback (Response), Diagnostic Tests, Cancer, Females
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Pálfi, Bence; Arora, Kavleen; Kostopoulou, Olga – Cognitive Research: Principles and Implications, 2022
Evidence-based algorithms can improve both lay and professional judgements and decisions, yet they remain underutilised. Research on advice taking established that humans tend to discount advice--especially when it contradicts their own judgement ("egocentric advice discounting")--but this can be mitigated by knowledge about the…
Descriptors: Physicians, Evidence Based Practice, Decision Making, Self Concept
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Branch, Fallon; Williams, K. Matthew; Santana, Isabella Noel; Hegdé, Jay – Cognitive Research: Principles and Implications, 2022
Many studies have shown that using a computer-aided detection (CAD) system does not significantly improve diagnostic accuracy in radiology, possibly because radiologists fail to interpret the CAD results properly. We tested this possibility using screening mammography as an illustrative example. We carried out two experiments, one using 28…
Descriptors: Radiology, Allied Health Personnel, Assistive Technology, Clinical Diagnosis