Multi-Center Study to Evaluate the Performance of DermDx for Primary Care Physicians in the Detection of Skin Cancers

Retrospective, Multi-Center Study to Evaluate the Performance of DermDx as an Adjunctive Tool for Primary Care Physicians in the Detection of Skin Cancers

The proposed study is a pivotal, multi-center retrospective reader study designed to determine whether the use of DermDx as a concurrent reading aid improves the performance of primary care physicians (PCPs) in diagnosing skin cancers.

The proposed study is a pivotal, multi-center retrospective reader study designed to determine whether the use of DermDx as a concurrent reading aid improves the performance of primary care physicians (PCPs) in diagnosing skin cancers.

DermDx is a deep learning-based algorithm that analyzes lesion images to detect skin cancer. The software does not have dedicated hardware and can accept as input any dermoscopic images taken with commercial dermoscopes.

Because the study is designed to investigate the change in the performance of the PCPs before and after seeing the device output, a single-arm study design has been used.

Inclusion criteria:

• The subjects must be Primary Care Physicians who are board certified in family medicine or internal medicine.

Exclusion criteria:

• Subjects not meeting inclusion criteria.