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Literature DB >> 28569993

A pretrained neural network shows similar diagnostic accuracy to medical students in categorizing dermatoscopic images after comparable training conditions.

P Tschandl¹, H Kittler¹, G Argenziano².

Abstract

Mesh：

Year: 2017 PMID： 28569993 DOI： 10.1111/bjd.15695

Source DB: PubMed Journal: Br J Dermatol ISSN： 0007-0963 Impact factor: 9.302

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Cited

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7 in total

Review 1. Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms: A Scoping Review.

Authors: Roxana Daneshjou; Mary P Smith; Mary D Sun; Veronica Rotemberg; James Zou
Journal: JAMA Dermatol Date: 2021-11-01 Impact factor: 11.816

2. Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.

Authors: Philipp Tschandl; Cliff Rosendahl; Bengu Nisa Akay; Giuseppe Argenziano; Andreas Blum; Ralph P Braun; Horacio Cabo; Jean-Yves Gourhant; Jürgen Kreusch; Aimilios Lallas; Jan Lapins; Ashfaq Marghoob; Scott Menzies; Nina Maria Neuber; John Paoli; Harold S Rabinovitz; Christoph Rinner; Alon Scope; H Peter Soyer; Christoph Sinz; Luc Thomas; Iris Zalaudek; Harald Kittler
Journal: JAMA Dermatol Date: 2019-01-01 Impact factor: 10.282

3. Fully automated segmentation of wrist bones on T2-weighted fat-suppressed MR images in early rheumatoid arthritis.

Authors: Lun Matthew Wong; Lin Shi; Fan Xiao; James Francis Griffith
Journal: Quant Imaging Med Surg Date: 2019-04

4. Performance of a deep neural network in teledermatology: a single-centre prospective diagnostic study.

Authors: C Muñoz-López; C Ramírez-Cornejo; M A Marchetti; S S Han; P Del Barrio-Díaz; A Jaque; P Uribe; D Majerson; M Curi; C Del Puerto; F Reyes-Baraona; R Meza-Romero; J Parra-Cares; P Araneda-Ortega; M Guzmán; R Millán-Apablaza; M Nuñez-Mora; K Liopyris; C Vera-Kellet; C Navarrete-Dechent
Journal: J Eur Acad Dermatol Venereol Date: 2020-11-22 Impact factor: 6.166

A pretrained neural network shows similar diagnostic accuracy to medical students in categorizing dermatoscopic images after comparable training conditions.

Review 1. Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms: A Scoping Review.

2. Expert-Level Diagnosis of Nonpigmented Skin Cancer by Combined Convolutional Neural Networks.

3. Fully automated segmentation of wrist bones on T2-weighted fat-suppressed MR images in early rheumatoid arthritis.

4. Performance of a deep neural network in teledermatology: a single-centre prospective diagnostic study.

Review 5. Dermatoscopy of Neoplastic Skin Lesions: Recent Advances, Updates, and Revisions.

6. A Novel Convolutional Neural Network for the Diagnosis and Classification of Rosacea: Usability Study.

Review 7. Artificial Intelligence Applications in Dermatology: Where Do We Stand?