Human–computer collaboration for skin cancer recognition

Analysis of Collective Human Intelligence for Diagnosis of Pigmented Skin Lesions Harnessed by Gamification Via a Web-Based Training Platform: Simulation Reader Study

(2020) Christoph Rinner et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

International evaluation of an AI system for breast cancer screening

(2020) Scott Mayer McKinney et al.   NATURE

Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders

(2020) Seung Seog Han et al.   JOURNAL OF INVESTIGATIVE DERMATOLOGY

Virtual health care in the era of COVID-19

(2020) Paul Webster   LANCET

Unmasking Clever Hans predictors and assessing what machines really learn

(2019) Sebastian Lapuschkin et al.   Nature Communications

Adversarial attacks on medical machine learning

(2019) Samuel G. Finlayson et al.   SCIENCE

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

Superior skin cancer classification by the combination of human and artificial intelligence

(2019) Achim Hekler et al.   EUROPEAN JOURNAL OF CANCER

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

Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm

(2018) Seung Seog Han et al.   JOURNAL OF INVESTIGATIVE DERMATOLOGY

Automated Dermatological Diagnosis: Hype or Reality?

(2018) Cristian Navarrete-Dechent et al.   JOURNAL OF INVESTIGATIVE DERMATOLOGY

Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images

(2018) Michael A. Marchetti et al.   JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY

Deep visual domain adaptation: A survey

(2018) Mei Wang et al.   NEUROCOMPUTING

Diagnostic Accuracy of Content Based Dermatoscopic Image Retrieval with Deep Classification Features

(2018) P Tschandl et al.   BRITISH JOURNAL OF DERMATOLOGY

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

(2018) Philipp Tschandl et al.   Scientific Data

The practical implementation of artificial intelligence technologies in medicine

(2018) Jianxing He et al.   NATURE MEDICINE

Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet

(2018) Nicholas Bien et al.   PLOS MEDICINE

Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks

(2017) Paras Lakhani et al.   RADIOLOGY

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs

(2016) Varun Gulshan et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION