Observational study investigating the level of support from a convolutional neural network in face and scalp lesions deemed diagnostically ‘unclear’ by dermatologists

The peculiar dermatoscopic pattern of scalp melanoma

(2022) I. Spyridis et al.   JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY

Clinical findings are not helpful in detecting lentigo maligna melanoma in patients with biopsy‐proven lentigo maligna

(2022) J. Zoutendijk et al.   JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY

Man against machine reloaded: performance of a market-approved convolutional neural network in classifying a broad spectrum of skin lesions in comparison with 96 dermatologists working under less artificial conditions

(2020) H.A. Haenssle et al.   ANNALS OF ONCOLOGY

Melanoma recognition by a deep learning convolutional neural network—Performance in different melanoma subtypes and localisations

(2020) Julia K. Winkler et al.   EUROPEAN JOURNAL OF CANCER

Dermoscopic predictors to discriminate between in situ and early invasive lentigo maligna melanoma: A retrospective observational study

(2020) Leonardo Peruilh-Bagolini et al.   JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY

The dermatoscopic inverse approach significantly improves the accuracy of human readers for lentigo maligna diagnosis

(2020) Aimilios Lallas et al.   JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY

Human–computer collaboration for skin cancer recognition

(2020) Philipp Tschandl et al.   NATURE MEDICINE

Skin lesions of face and scalp – Classification by a market-approved convolutional neural network in comparison with 64 dermatologists

(2020) Holger Andreas Haenssle et al.   EUROPEAN JOURNAL OF CANCER

Computer Algorithms Show Potential for Improving Dermatologists’ Accuracy to Diagnose Cutaneous Melanoma; Results of ISIC 2017

(2019) Michael A. Marchetti et al.   JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY

Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study

(2019) Philipp Tschandl et al.   LANCET ONCOLOGY

Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition

(2019) Julia K. Winkler et al.   JAMA Dermatology

Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

(2018) H A Haenssle et al.   ANNALS OF ONCOLOGY

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

Dermoscopic clues to differentiate facial lentigo maligna from pigmented actinic keratosis

(2016) A. Lallas et al.   BRITISH JOURNAL OF DERMATOLOGY

Dermatoscopy of flat pigmented facial lesions

(2014) P. Tschandl et al.   JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY

Basic histological structure and functions of facial skin

(2013) Oktay Arda et al.   CLINICS IN DERMATOLOGY

World Medical Association Declaration of Helsinki

(2013)   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION