Literature DB >> 24163062

A prospective study of mobile phones for dermatology in a clinical setting.

Jessika Weingast1, Christian Scheibböck, Elisabeth M T Wurm, Elisabeth Ranharter, Stefanie Porkert, Stephan Dreiseitl, Christian Posch, Michael Binder.   

Abstract

We evaluated the accuracy of diagnoses made from pictures taken with the built-in cameras of mobile phones in a 'real-life' clinical setting. A total of 263 patients took part, who photographed their own lesions where possible, and provided clinical information via a questionnaire. After the teledermatology procedure, each patient was examined face-to-face and a gold standard diagnosis was made. The telemedicine data and pictures were diagnosed by 15 dermatologists. The 299 cases contained 1-22 clinical images each (median 3). Nine dermatologists finished all the cases and the remaining six completed some of them, thus providing 2893 decisions. Overall, 61% of all cases were rated as possible to diagnose and of those, 80% were correct in comparison with the face-to-face diagnosis. Image quality was evaluated and the median was 5 on a 10-point scale. There was a significant correlation between the correct diagnosis and the quality of the photographs taken (P < 0.001). In nearly two-thirds of all cases, a teledermatology diagnosis was possible; however, there was insufficient information to make a telemedicine diagnosis in about one-third of the cases. If applied carefully, mobile phones could be a powerful tool for people to optimize their health care status.

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Mesh:

Year:  2013        PMID: 24163062     DOI: 10.1177/1357633x13490890

Source DB:  PubMed          Journal:  J Telemed Telecare        ISSN: 1357-633X            Impact factor:   6.184


  6 in total

Review 1.  The Empirical Foundations of Teledermatology: A Review of the Research Evidence.

Authors:  Rashid L Bashshur; Gary W Shannon; Trilokraj Tejasvi; Joseph C Kvedar; Michael Gates
Journal:  Telemed J E Health       Date:  2015-09-22       Impact factor: 3.536

2.  Teledermatology for diagnosing skin cancer in adults.

Authors:  Naomi Chuchu; Jacqueline Dinnes; Yemisi Takwoingi; Rubeta N Matin; Susan E Bayliss; Clare Davenport; Jacqueline F Moreau; Oliver Bassett; Kathie Godfrey; Colette O'Sullivan; Fiona M Walter; Richard Motley; Jonathan J Deeks; Hywel C Williams
Journal:  Cochrane Database Syst Rev       Date:  2018-12-04

3.  Part II: Accuracy of Teledermatology in Skin Neoplasms.

Authors:  Mara Giavina-Bianchi; Maria Fernanda Dias Azevedo; Raquel Machado Sousa; Eduardo Cordioli
Journal:  Front Med (Lausanne)       Date:  2020-11-23

Review 4.  Store-and-Forward Images in Teledermatology: Narrative Literature Review.

Authors:  Simon W Jiang; Michael Seth Flynn; Jeffery T Kwock; Matilda W Nicholas
Journal:  JMIR Dermatol       Date:  2022-07-18

Review 5.  Skin Cancer Classification With Deep Learning: A Systematic Review.

Authors:  Yinhao Wu; Bin Chen; An Zeng; Dan Pan; Ruixuan Wang; Shen Zhao
Journal:  Front Oncol       Date:  2022-07-13       Impact factor: 5.738

6.  Part I: Accuracy of Teledermatology in Inflammatory Dermatoses.

Authors:  Mara Giavina-Bianchi; Raquel Sousa; Eduardo Cordioli
Journal:  Front Med (Lausanne)       Date:  2020-10-27
  6 in total

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