The DOI matches its Crossref record.
Digital oncology apps: revolution or evolution?
Open accessAbstract
The UK's recent spell of hot and sunny weather serves as a reminder of the need to be cognisant of the association between increased sun exposure and heightened skin cancer risk. In a timely study presented at the British Association of Dermatologists' 98th Annual Meeting (July 3–5, 2018; Edinburgh, UK), researchers evaluated the increasing number of new digital apps to aid in skin cancer diagnosis that are entering the digital oncology market. Could such technologies revolutionise the detection and treatment of this disease? And how much do they—and the rapidly emerging digital health market as a whole—add to existing standards of care?
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Current evidence is not at a level to suggest that apps screening photographs could replace a clinical consultation.
“However, experts have highlighted that current evidence is not at a level to suggest that apps screening photographs could replace a clinical consultation.”
From What is the clinical value of mHealth for patients? (2020) · cites this paper as [6]
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What is the clinical value of mHealth for patients?
Rowland, S. P., Fitzgerald, J. E., Holme, T., Powell, J., & McGregor, A. (2020) · npj Digital Medicine · doi:10.1038/s41746-019-0206-x · Cited by 454
Metadata
- Authors
- Oncology, T. L.
- Corresponding author
- The Lancet Oncology
- Venue
- The Lancet Oncology
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 19
- Issue
- 8
- Pages
- 999
- ISSN
- 1470-2045 (ISSN-L)
- OpenAlex
- W4248717326
- Cited by
- 4
- References
- 0
- Citations by year
- 2021: 1 · 2020: 2 · 2019: 1
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The Lancet Oncology (publishedVersion, public-domain)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cutaneous Melanoma Detection and Management
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- skin cancer, skin cancer diagnosis, mobile health, sun exposure, skin cancer risk, cancer detection, standard of care
- MeSH terms
- Humans, Medical Oncology, Mobile Applications
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