A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task

Citations Over TimeTop 1% of 2019 papers

Abstract

For the first time, dermatologist-level image classification was achieved on a clinical image classification task without training on clinical images. The CNN had a smaller variance of results indicating a higher robustness of computer vision compared with human assessment for dermatologic image classification tasks.

Related Papers

• → The misdiagnosis of malignant melanoma(1999)84 cited
• → Early detection of malignant melanoma(1976)65 cited
• [Delay in diagnosing melanoma. A prospective study in 102 patients].(1997)
• → CYTODIAGNOSIS OF MALIGNANT MELANOMA BY THE TOUCH‐FLUORESCENCE METHOD(1985)8 cited
• Desmoplastic melanoma (or is it merely cicatrix?) arising at the site of biopsy within a conventional melanoma: pitfalls in the diagnosis desmoplastic melanoma.(1995)