Screening efficiency over experience: Rapid target detection in low-power field as a modifiable cognitive biomarker for diagnostic accuracy in digital cytology

Abstract

Background: Traditionally, cytology expertise has been equated with professional experience. However, the transition to whole-slide imaging and artificial intelligence (AI) necessitates a shift from exhaustive screening to rapid verification. The goal of this study was to identify cognitive biomarkers associated with diagnostic accuracy and evaluate their modifiability. Methods: In phase 1, 100 cytotechnologists with 1–40 years of experience diagnosed 30 digital cytology images using eye-tracking. Gaze metrics across areas of interest were analyzed via nominal logistic regression. In phase 2, 28 students completed a 3-month cytotechnology training program. Pre- and post-training metrics were compared using Wilcoxon signed-rank tests and effect sizes (r). Results: Years of experience showed no significant correlation with diagnostic accuracy (r = 0.189, p >.05). Multivariate analysis identified shorter total fixation duration on the “low-power field (LPF) main object” as the sole independent predictor of high accuracy (p =.045), suggesting a “pop-out” detection mechanism. Experience correlated only with attention to sample information. Post-training (phase 2), students' time to first target fixation decreased substantially (r = 0.62–0.86), whereas their attention to normal backgrounds decreased (r = 0.71). This demonstrates the rapid acquisition of expert-like selective attention. Conclusions: Efficiency in LPF target detection is a better predictor of diagnostic accuracy than professional experience. This study identifies LPF efficiency as a modifiable cognitive biomarker that can be acquired through standard education. Quantifying these gaze metrics provides an objective means of evaluating skill development and readiness for the AI era.