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For: Thissen M, Udrea A, Hacking M, von Braunmuehl T, Ruzicka T. mHealth App for Risk Assessment of Pigmented and Nonpigmented Skin Lesions-A Study on Sensitivity and Specificity in Detecting Malignancy. Telemed J E Health 2017;23:948-54. [PMID: 28562195 DOI: 10.1089/tmj.2016.0259] [Cited by in Crossref: 27] [Cited by in F6Publishing: 22] [Article Influence: 5.4] [Reference Citation Analysis]
Number Citing Articles
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9 Wen H, Yu W, Wu Y, Jun Z, Liu X, Kuang Z, Fan R. Acne detection and severity evaluation with interpretable convolutional neural network models. Technol Health Care 2022. [PMID: 35124592 DOI: 10.3233/THC-228014] [Reference Citation Analysis]
10 Steeb T, Wessely A, Mastnik S, Brinker TJ, French LE, Niesert AC, Berking C, Heppt MV. Patient Attitudes and Their Awareness Towards Skin Cancer-Related Apps: Cross-Sectional Survey. JMIR Mhealth Uhealth 2019;7:e13844. [PMID: 31267978 DOI: 10.2196/13844] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
11 Zink A, Kolbinger A, Leibl M, Léon Suarez I, Gloning J, Merkel C, Winkler J, Biedermann T, Ring J, Eberlein B. Teledermatoskopie mittels Smartphone: Zuverlässige Hilfe bei der Diagnostik von Hautläsionen? Hautarzt 2017;68:890-5. [DOI: 10.1007/s00105-017-4042-0] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 1.4] [Reference Citation Analysis]
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13 Chung Y, van der Sande AAJ, de Roos KP, Bekkenk MW, de Haas ERM, Kelleners-Smeets NWJ, Kukutsch NA. Poor agreement between the automated risk assessment of a smartphone application for skin cancer detection and the rating by dermatologists. J Eur Acad Dermatol Venereol 2020;34:274-8. [PMID: 31423673 DOI: 10.1111/jdv.15873] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.7] [Reference Citation Analysis]
14 de Carvalho TM, Noels E, Wakkee M, Udrea A, Nijsten T. Development of Smartphone Apps for Skin Cancer Risk Assessment: Progress and Promise. JMIR Dermatol 2019;2:e13376. [DOI: 10.2196/13376] [Cited by in Crossref: 7] [Cited by in F6Publishing: 2] [Article Influence: 2.3] [Reference Citation Analysis]
15 Moura P, Fazendeiro P, Inácio PRM, Vieira-Marques P, Ferreira A. Assessing Access Control Risk for mHealth: A Delphi Study to Categorize Security of Health Data and Provide Risk Assessment for Mobile Apps. J Healthc Eng 2020;2020:5601068. [PMID: 32015795 DOI: 10.1155/2020/5601068] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
16 Akbar S, Coiera E, Magrabi F. Safety concerns with consumer-facing mobile health applications and their consequences: a scoping review. J Am Med Inform Assoc 2020;27:330-40. [PMID: 31599936 DOI: 10.1093/jamia/ocz175] [Cited by in Crossref: 32] [Cited by in F6Publishing: 18] [Article Influence: 32.0] [Reference Citation Analysis]
17 Shlivko IL, Garanina OY, Klemenova IA, Uskova KA, Mironycheva AM, Dardyk VI, Laskov VN. Artificial intelligence: how it works and criteria for assessment. Consilium Medicum 2021;23:626-32. [DOI: 10.26442/20751753.2021.8.201148] [Reference Citation Analysis]
18 Brinker TJ, Schadendorf D, Klode J, Cosgarea I, Rösch A, Jansen P, Stoffels I, Izar B. Photoaging Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study. JMIR Mhealth Uhealth 2017;5:e101. [PMID: 28747297 DOI: 10.2196/mhealth.8231] [Cited by in Crossref: 22] [Cited by in F6Publishing: 20] [Article Influence: 4.4] [Reference Citation Analysis]
19 Chu YS, An HG, Oh BH, Yang S. Artificial Intelligence in Cutaneous Oncology. Front Med (Lausanne) 2020;7:318. [PMID: 32754606 DOI: 10.3389/fmed.2020.00318] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
20 Udrea A, Mitra GD, Costea D, Noels EC, Wakkee M, Siegel DM, de Carvalho TM, Nijsten TEC. Accuracy of a smartphone application for triage of skin lesions based on machine learning algorithms. J Eur Acad Dermatol Venereol 2020;34:648-55. [PMID: 31494983 DOI: 10.1111/jdv.15935] [Cited by in Crossref: 20] [Cited by in F6Publishing: 13] [Article Influence: 6.7] [Reference Citation Analysis]
21 Freeman K, Dinnes J, Chuchu N, Takwoingi Y, Bayliss SE, Matin RN, Jain A, Walter FM, Williams HC, Deeks JJ. Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies. BMJ 2020;368:m127. [PMID: 32041693 DOI: 10.1136/bmj.m127] [Cited by in Crossref: 46] [Cited by in F6Publishing: 31] [Article Influence: 23.0] [Reference Citation Analysis]
22 Rat C, Hild S, Rault Sérandour J, Gaultier A, Quereux G, Dreno B, Nguyen JM. Use of Smartphones for Early Detection of Melanoma: Systematic Review. J Med Internet Res 2018;20:e135. [PMID: 29653918 DOI: 10.2196/jmir.9392] [Cited by in Crossref: 42] [Cited by in F6Publishing: 33] [Article Influence: 10.5] [Reference Citation Analysis]
23 Moayedi-Nia S, Barss L, Oxlade O, Valiquette C, Ly MX, Campbell JR, Lan Z, Nsengiyumva P, Fregonese F, Lisboa Bastos M, Sampath D, Winters N, Menzies D. The mTST - An mHealth approach for training and quality assurance of tuberculin skin test administration and reading. PLoS One 2019;14:e0215240. [PMID: 30995275 DOI: 10.1371/journal.pone.0215240] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
24 Rubagumya F, Nyagabona SK, Longombe AN, Manirakiza A, Ngowi J, Maniragaba T, Sabushimike D, Urusaro S, Ndoli DA, Dharsee N, Mwaiselage J, Mavura D, Hanna TP, Hammad N. Feasibility Study of a Smartphone Application for Detecting Skin Cancers in People With Albinism. JCO Glob Oncol 2020;6:1370-5. [PMID: 32903120 DOI: 10.1200/GO.20.00264] [Reference Citation Analysis]