Caution in melanoma risk analysis with smartphone application technology: Correspondence
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For apps with uncertain availability or withdrawn apps, MelApp had low sensitivities (25-50%) and Mole Detective, Dr Mole, and SpotMole had low specificities (20-60%).
“with either low sensitivities (25-50% for MelApp) or specificities (20-60% for Mole Detective, Dr Mole, and SpotMole).”
From Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies (2020) · cites this paper as [32]
Results from the five studies that reported data for apps with uncertain availability or withdrawn apps are if anything more variable.
“Results from the five studies that reported data for apps with uncertain availability23 24 or withdrawn apps23 32 are if anything more variable.”
From Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies (2020) · cites this paper as [32]
Smartphone apps for melanoma detection could actually harm users, for example by providing inaccurate or misleading advice, being used as a substitute for clinical consultation, or delaying melanoma diagnosis.
“The advice could be inaccurate or misleading, apps could be used as a substitute for a clinical consultation, and they could even delay melanoma diagnosis.12”
From Smartphone applications for melanoma detection by community, patient and generalist clinician users: a review (2015) · cites this paper as [12]
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“Likewise, Robson et al. [ 95 ] and Wolf et al. [ 39 ] urged caution when using melanoma risk analysis and detection apps due to their diagnostic inaccuracy.”
MethodSmartphone Sensors for Health Monitoring and Diagnosis
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“A detailed review of smartphone-based fall detection systems was presented in References [161,162].”
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“Attempts are being made to utilize them in clinical scenarios with varying degrees of success, particularly in dermatology [2] and ophthalmology [3, 4].”
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Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma
Chuchu, N., Takwoingi, Y., Dinnes, J., Matin, R. N., Bassett, O., Moreau, J. F., Bayliss, S. E., Davenport, C., Godfrey, K., O'Connell, S., et al. (2018) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd013192 · Cited by 144 · see citing works
Mobile applications in dermatology
Brewer, A. C., Endly, D. C., Henley, J., Amir, M., Sampson, B. P., Moreau, J. F., & Dellavalle, R. P. (2013) · JAMA Dermatology · doi:10.1001/jamadermatol.2013.5517 · Cited by 121 · see citing works
Artificial Intelligence in Skin Cancer Diagnosis: A Reality Check
Brancaccio, G., Balato, A., Malvehy, J., Puig, S., Argenziano, G., & Kittler, H. (2023) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2023.10.004 · Cited by 137 · see citing works
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“This is of particular importance for apps designed to have a direct impact on clinical decision-making, including medication dose calculation, adjustment of therapy, and for diagnostic purposes [12,13].”
BackgroundUse of Smartphones for Early Detection of Melanoma: Systematic Review
Rat, C., Hild, S., Rault Sérandour, J., Gaultier, A., Quereux, G., Dreno, B., & Nguyen, J.-M. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9392 · Cited by 107 · see citing works
“In these, 12 studies had been conducted in European countries, that is, Great Britain [34,53], Austria [38,41], Sweden [29,35], Ireland [50], Germany [51], Switzerland [40], Greece [44], the Netherlands [54], and France [36]; 7 in United States of America [32,42,45-49]; 5 in Australia [31,33,37,39,52]; and one in Sing…”
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Smart Phone Applications as a Source of Information on Stroke
Dubey, D., Amritphale, A., Sawhney, A., Amritphale, N., Dubey, P. K., & Pandey, A. (2014) · Journal of Stroke · doi:10.5853/jos.2014.16.2.86 · Cited by 74 · see citing works
Practical application of new technologies for melanoma diagnosis
March, J., Hand, M., & Grossman, D. (2015) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2015.02.1138 · Cited by 72 · see citing works
Smartphone applications for cancer patients; what we know about them?
Collado‐Borrell, R., Escudero‐Vilaplana, V., Ribed-Sánchez, A., Ibáñez-García, S., Alonso, A. H., & Sanjurjo‐Sáez, M. (2016) · PubMed · doi:10.7399/fh.2016.40.1.8993 · Cited by 66 · see citing works
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Posttraumatic Stress Disorder and Mobile Health: App Investigation and Scoping Literature Review
Rodriguez-Paras, C., Tippey, K., Brown, E., Sasangohar, F., Creech, S., Kum, H.-C., Lawley, M., & Benzer, J. K. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.7318 · Cited by 58 · see citing works
“…and financial considerations. mHealth apps have thus far been successfully implemented across a wide range of medical disciplines, including dermatology [1], ophthalmology [2], and nutritional sciences [3] and have addressed many specific illnesses such as diabetes [4] and infectious diseases [5].”
BackgroundEfficacy of smartphone applications in high-risk pigmented lesions
Ngoo, A., Finnane, A., McMeniman, E., Tan, J., Janda, M., & Soyer, H. P. (2018) · Australasian Journal of Dermatology · doi:10.1111/ajd.12599 · Cited by 55 · see citing works
“Characteristics of participants Recruitment location Total n = 30, n (%) BNMS study n = 12, n (%) Dermatology OPD Surgical list n = 18, n (%) Gender n = 30 (%) Male 3 (10) 10 (33) 13 (43) Female 9 (30) 8 (27) 17 (57) Age n = 30 (%) 20–29 1 (3) 0 (0) 1 (3) 30–39 1 (3) 1 (3) 2 (7) 40–49 3 (10) 2 (7) 5 (17) 50–59 3 (10)…”
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Popularity and impact of using smart devices in medicine: experiences in Saudi Arabia
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Artificial Intelligence Approach in Melanoma
Curiel‐Lewandrowski, C. N., Novoa, R. A., Berry, E., Celebi, M. E., Codella, N., Giuste, F., Gutman, D. A., Halpern, A. C., Leachman, S. A., Liu, Y., et al. (2019) · Springer eBooks · doi:10.1007/978-1-4614-7322-0_43-1 · Cited by 20 · see citing works
Mobile Medical Applications for Melanoma Risk Assessment: False Assurance or Valuable Tool?
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“This issue, which was a phenomenon observed during our data collection has been briefly addressed in one previous study [13].”
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Mobile Teledermatology is a Valid Method to Estimate Prevalence of Melanocytic Naevi in Children
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“However, the quality of the images can vary and especially mobile applications with automatic diagnostic algorithms linked have been questioned (12, 13).”
BackgroundMobile Technology for the Practice of Pathology
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Challenges to smartphone applications for melanoma detection
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“Another is a consumer melanoma application that allows individuals to use the camera on their smartphones to take a picture of a skin lesion or mole to get a preliminary diagnosis [3].”
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Smartphone diagnosis of skin cancer: there's not yet an app for that
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Usability Assessment of a Post-Traumatic Stress Disorder (PTSD) mHealth App
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“reported a smartphone application for assessing melanoma risk [14].”
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Early Melanoma Detection Based on Chromatic Descriptors and Machine Learning Algorithms
Udrea, A. (2015) · Journal of Control Engineering and Applied Informatics
- Authors
- Robson, Y., Blackford, S., & Roberts, D.
- Affiliations
- Singleton Hospital (GB)
- Corresponding author
- Robson, Y.
- Blackford, S.
- Roberts, D.
- Venue
- British Journal of Dermatology
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-07-05
- Volume
- 167
- Issue
- 3
- Pages
- 703-704
- ISSN
- 0007-0963 (ISSN-L)
- OpenAlex
- W2128507689
- Cited by
- 39
- References
- 2
- Citations by year
- 2023: 1 · 2021: 1 · 2020: 1 · 2019: 3 · 2018: 4 · 2017: 7 · 2016: 3 · 2015: 7 · 2014: 8 · 2013: 3 · 2012: 1
- FWCI
- 3.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- British Journal of Dermatology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › melanin and skin pigmentation
- Keywords
- melanoma, melanoma risk assessment, mobile application, mobile health, skin cancer screening, digital health tools
- MeSH terms
- Diagnosis, Computer-Assisted, Humans, Melanoma, Sensitivity and Specificity, Skin Neoplasms, Software, Telemedicine, Risk Assessment, Computers, Handheld, Cell Phone
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