The Impact of Melanoma Imaging Biomarker Cues on Detection Sensitivity and Specificity in Melanoma versus Clinically Atypical Nevi.

ABSTRACT: Incorporation of dermoscopy and artificial intelligence (AI) is improving healthcare professionals' ability to diagnose melanoma earlier, but these algorithms often suffer from a "black box" issue, where decision-making processes are not transparent, limiting their utility for training healthcare providers. To address this, an automated approach for generating melanoma imaging biomarker cues (IBCs), which mimics the screening cues used by expert dermoscopists, was developed. This study created a one-minute learning environment where dermatologists adopted a sensory cue integration algorithm to combine a single IBC with a risk score built on many IBCs, then immediately tested their performance in differentiating melanoma from benign nevi. Ten participants evaluated 78 dermoscopic images, co

SUBMITTER: Aguero R 

PROVIDER: S-EPMC11394255 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature