Literature DB >> 18486022

Automated diagnostic instruments for cutaneous melanoma.

Malene E Vestergaard1, Scott W Menzies.   

Abstract

The objective of this review is to report and discuss the evidence for fully automated diagnostic instruments for cutaneous melanoma tested in a real-world clinical setting directly compared with human diagnosis. A systematic review was performed and articles excluded when studies did not report sensitivity or specificity for melanoma directly compared with humans on an independent test set. Only 3 instruments have had their diagnostic accuracy compared with a human diagnosis in the clinical field with a meaningful sample size that could allow some generalization with the wider clinical arena. Two of these instruments showed a significantly inferior specificity for the diagnosis of melanoma compared with specialists. In one of these studies, the sensitivity for diagnosis, although superior to the specialist diagnosis, did not reach statistical significance. In contrast, one instrument had an equivalent specificity and trended superior but not significantly for sensitivity for the diagnosis of melanoma. Other image based nonclinic studies and studies comparing clinical management as the endpoint rather than diagnosis are also reviewed.

Entities:  

Mesh:

Year:  2008        PMID: 18486022     DOI: 10.1016/j.sder.2008.01.001

Source DB:  PubMed          Journal:  Semin Cutan Med Surg        ISSN: 1085-5629


  8 in total

Review 1.  Artificial intelligence in dermatology and healthcare: An overview.

Authors:  Varadraj Vasant Pai; Rohini Bhat Pai
Journal:  Indian J Dermatol Venereol Leprol       Date:  2021 [SEASON]       Impact factor: 2.545

2.  Noninvasive genomic detection of melanoma.

Authors:  W Wachsman; V Morhenn; T Palmer; L Walls; T Hata; J Zalla; R Scheinberg; H Sofen; S Mraz; K Gross; H Rabinovitz; D Polsky; S Chang
Journal:  Br J Dermatol       Date:  2011-03-25       Impact factor: 9.302

3.  Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults.

Authors:  Lavinia Ferrante di Ruffano; Yemisi Takwoingi; Jacqueline Dinnes; Naomi Chuchu; Susan E Bayliss; Clare Davenport; Rubeta N Matin; Kathie Godfrey; Colette O'Sullivan; Abha Gulati; Sue Ann Chan; Alana Durack; Susan O'Connell; Matthew D Gardiner; Jeffrey Bamber; Jonathan J Deeks; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

4.  Computer-Aided Decision Support for Melanoma Detection Applied on Melanocytic and Nonmelanocytic Skin Lesions: A Comparison of Two Systems Based on Automatic Analysis of Dermoscopic Images.

Authors:  Kajsa Møllersen; Herbert Kirchesch; Maciel Zortea; Thomas R Schopf; Kristian Hindberg; Fred Godtliebsen
Journal:  Biomed Res Int       Date:  2015-11-26       Impact factor: 3.411

5.  Differentiation of benign pigmented skin lesions with the aid of computer image analysis: a novel approach.

Authors:  Jae Woo Choi; Young Woon Park; Sang Young Byun; Sang Woong Youn
Journal:  Ann Dermatol       Date:  2013-08-13       Impact factor: 1.444

6.  Dermoscopy use in UK primary care: a survey of GPs with a special interest in dermatology.

Authors:  O T Jones; L C Jurascheck; M Utukuri; M M Pannebakker; J Emery; F M Walter
Journal:  J Eur Acad Dermatol Venereol       Date:  2019-05-17       Impact factor: 6.166

7.  Dermoscopy for melanoma detection and triage in primary care: a systematic review.

Authors:  O T Jones; L C Jurascheck; M A van Melle; S Hickman; N P Burrows; P N Hall; J Emery; F M Walter
Journal:  BMJ Open       Date:  2019-08-20       Impact factor: 2.692

Review 8.  Computer aided diagnostic support system for skin cancer: a review of techniques and algorithms.

Authors:  Ammara Masood; Adel Ali Al-Jumaily
Journal:  Int J Biomed Imaging       Date:  2013-12-23
  8 in total

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