Table 1.xls (5.5 kB)
Summary of results for each image viewed.
dataset
posted on 2024-02-27, 19:01 authored by Dat Duong, Anna Rose Johny, Suzanna Ledgister Hanchard, Christopher Fortney, Kendall Flaharty, Fabio Hellmann, Ping Hu, Behnam Javanmardi, Shahida Moosa, Tanviben Patel, Susan Persky, Ömer Sümer, Cedrik Tekendo-Ngongang, Hellen Lesmann, Tzung-Chien Hsieh, Rebekah L. Waikel, Elisabeth André, Peter Krawitz, Benjamin D. SolomonFor a specific image, we count the number of clinicians and non-clinicians who correctly and incorrectly identified that this image is of an affected or unaffected individual. Column Identified condition name indicates the number of clinicians and non-clinicians who correctly identified the specific condition. As eye-tracking results for seven individual images had to be discarded for technical reasons, not every image has a complete data from 22 clinicians and 22 non-clinicians. The images are listed in the order shown to the participants.
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two participant groupskullback &# 8211high accuracy ratedeep learning classifiercurrent approaches focuspotential genetic conditionsindividuals also tendcomputer visual attentionclinicians versus noncomputer attentionvisual attentionsunaffected individualsmany conditionstracking analysestechnology assessesstudy showsspecific patternsaliency resultssaliency mapsperformed eyeone typemeaningful interactionsleibler divergenceincreasingly usedimage inspectiongenetics clinicgeneticist cliniciansfacial diagnosticsevaluate patientsdifferent levelsclinician groupclinical geneticist
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