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For: Buechi R, Faes L, Bachmann LM, Thiel MA, Bodmer NS, Schmid MK, Job O, Lienhard KR. Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis. BMJ Open 2017;7:e018280. [PMID: 29247099 DOI: 10.1136/bmjopen-2017-018280] [Cited by in Crossref: 28] [Cited by in F6Publishing: 19] [Article Influence: 5.6] [Reference Citation Analysis]
Number Citing Articles
1 Jukic T, Ihan A, Strojnik V, Stubljar D, Starc A. The effect of active occupational stress management on psychosocial and physiological wellbeing: a pilot study. BMC Med Inform Decis Mak 2020;20:321. [PMID: 33272279 DOI: 10.1186/s12911-020-01347-z] [Reference Citation Analysis]
2 Longoni L, Brunati R, Sale P, Casale R, Ronconi G, Ferriero G. Smartphone applications validated for joint angle measurement: a systematic review. Int J Rehabil Res 2019;42:11-9. [PMID: 30640272 DOI: 10.1097/MRR.0000000000000332] [Cited by in Crossref: 11] [Cited by in F6Publishing: 2] [Article Influence: 3.7] [Reference Citation Analysis]
3 Jinnai S, Yamazaki N, Hirano Y, Sugawara Y, Ohe Y, Hamamoto R. The Development of a Skin Cancer Classification System for Pigmented Skin Lesions Using Deep Learning. Biomolecules. 2020;10. [PMID: 32751349 DOI: 10.3390/biom10081123] [Cited by in Crossref: 14] [Cited by in F6Publishing: 12] [Article Influence: 7.0] [Reference Citation Analysis]
4 Bondaronek P, Slee A, Hamilton FL, Murray E. Relationship between popularity and the likely efficacy: an observational study based on a random selection on top-ranked physical activity apps. BMJ Open 2019;9:e027536. [PMID: 31727641 DOI: 10.1136/bmjopen-2018-027536] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 1.3] [Reference Citation Analysis]
5 Alamoodi AH, Garfan S, Zaidan BB, Zaidan AA, Shuwandy ML, Alaa M, Alsalem MA, Mohammed A, Aleesa AM, Albahri OS, Al-hussein WA, Alobaidi OR. A systematic review into the assessment of medical apps: motivations, challenges, recommendations and methodological aspect. Health Technol 2020;10:1045-61. [DOI: 10.1007/s12553-020-00451-4] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
6 Karim JL, Talhouk A. Person-Generated Health Data in Women's Health: Protocol for a Scoping Review. JMIR Res Protoc 2021;10:e26110. [PMID: 34047708 DOI: 10.2196/26110] [Reference Citation Analysis]
7 Lowe C, Hanuman Sing H, Browne M, Alwashmi MF, Marsh W, Morrissey D. Usability Testing of a Digital Assessment Routing Tool: Protocol for an Iterative Convergent Mixed Methods Study. JMIR Res Protoc 2021;10:e27205. [PMID: 34003135 DOI: 10.2196/27205] [Reference Citation Analysis]
8 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]
9 Helweg-Jørgensen S, Beck Lichtenstein M, Fruzzetti AE, Møller Dahl C, Pedersen SS. Daily Self-Monitoring of Symptoms and Skills Learning in Patients With Borderline Personality Disorder Through a Mobile Phone App: Protocol for a Pragmatic Randomized Controlled Trial. JMIR Res Protoc 2020;9:e17737. [PMID: 32449690 DOI: 10.2196/17737] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 2.5] [Reference Citation Analysis]
10 Hogarty DT, Hogarty JP, Hewitt AW. Smartphone use in ophthalmology: What is their place in clinical practice? Survey of Ophthalmology 2020;65:250-62. [DOI: 10.1016/j.survophthal.2019.09.001] [Cited by in Crossref: 14] [Cited by in F6Publishing: 17] [Article Influence: 7.0] [Reference Citation Analysis]
11 Ana FA, Loreto MS, José LM, Pablo SM, María Pilar MJ, Myriam SA. Mobile applications in oncology: A systematic review of health science databases. Int J Med Inform 2020;133:104001. [PMID: 31706229 DOI: 10.1016/j.ijmedinf.2019.104001] [Cited by in Crossref: 14] [Cited by in F6Publishing: 7] [Article Influence: 4.7] [Reference Citation Analysis]
12 Fujisawa Y, Otomo Y, Ogata Y, Nakamura Y, Fujita R, Ishitsuka Y, Watanabe R, Okiyama N, Ohara K, Fujimoto M. Deep-learning-based, computer-aided classifier developed with a small dataset of clinical images surpasses board-certified dermatologists in skin tumour diagnosis. Br J Dermatol. 2019;180:373-381. [PMID: 29953582 DOI: 10.1111/bjd.16924] [Cited by in Crossref: 93] [Cited by in F6Publishing: 66] [Article Influence: 23.3] [Reference Citation Analysis]
13 Mercurio M, Larsen M, Wisniewski H, Henson P, Lagan S, Torous J. Longitudinal trends in the quality, effectiveness and attributes of highly rated smartphone health apps. Evid Based Ment Health 2020;23:107-11. [PMID: 32312794 DOI: 10.1136/ebmental-2019-300137] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
14 Lowe C, Hanuman Sing H, Marsh W, Morrissey D. Validation of a Musculoskeletal Digital Assessment Routing Tool: Protocol for a Pilot Randomized Crossover Noninferiority Trial. JMIR Res Protoc 2021;10:e31541. [PMID: 34898461 DOI: 10.2196/31541] [Reference Citation Analysis]
15 Cazzaniga S, Castelli E, Di Landro A, Di Mercurio M, Imberti G, Locatelli GA, Raponi F, Vezzoli P, Gambini D, Damiani G, Zucchi A, Naldi L. Mobile teledermatology for melanoma detection: Assessment of the validity in the framework of a population-based skin cancer awareness campaign in northern Italy. J Am Acad Dermatol 2019;81:257-60. [PMID: 30797846 DOI: 10.1016/j.jaad.2019.02.036] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
16 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]
17 Barnett S, Huckvale K, Christensen H, Venkatesh S, Mouzakis K, Vasa R. Intelligent Sensing to Inform and Learn (InSTIL): A Scalable and Governance-Aware Platform for Universal, Smartphone-Based Digital Phenotyping for Research and Clinical Applications. J Med Internet Res 2019;21:e16399. [PMID: 31692450 DOI: 10.2196/16399] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 2.7] [Reference Citation Analysis]
18 Pipitprapat W, Harnchoowong S, Suchonwanit P, Sriphrapradang C. The validation of smartphone applications for heart rate measurement. Ann Med 2018;50:721-7. [PMID: 30269602 DOI: 10.1080/07853890.2018.1531144] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 1.8] [Reference Citation Analysis]
19 Rowland SP, Fitzgerald JE, Holme T, Powell J, McGregor A. What is the clinical value of mHealth for patients? NPJ Digit Med 2020;3:4. [PMID: 31970289 DOI: 10.1038/s41746-019-0206-x] [Cited by in Crossref: 56] [Cited by in F6Publishing: 32] [Article Influence: 28.0] [Reference Citation Analysis]
20 Corneli P, Zalaudek I, Magaton Rizzi G, di Meo N. Improving the early diagnosis of early nodular melanoma: can we do better? Expert Review of Anticancer Therapy 2018;18:1007-12. [DOI: 10.1080/14737140.2018.1507822] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
21 Jazayeri SMHM, Jamshidnezhad A. Top Mobile Applications in Pediatrics and Children's Health: Assessment and Intelligent Analysis Tools for a Systematic Investigation. Malays J Med Sci 2019;26:5-14. [PMID: 30914890 DOI: 10.21315/mjms2019.26.1.2] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]