ArticleNPJ digital medicine2023
An artificial intelligence based app for skin cancer detection evaluated in a population based setting.
Article in NPJ digital medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 74 citations in OpenAlex.
- Diagnosis melanoma with artificial intelligence systems: A meta-analysis study and systematic review.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025Pooled it
- Pooled it
- Consumer Understanding of Skin Concerns With an AI-Powered Informational Tool.JAMA dermatology · 2026Trial
- Attention guided fair artificial intelligence modeling for skin cancer diagnosis.NPJ digital medicine · 2026Article
- Artificial intelligence for detecting fetal orofacial clefts and advancing medical education.Nature communications · 2026Article
- Personalised health plan development using agentic AI in Singapore's national preventive care programme: a pilot study.NPJ digital medicine · 2026Article
- Quercetin and Its Nano-Based Formulations Against Skin Cancer: A Narrative Review.Health science reports · 2026Article
- Multimodal artificial intelligence for enhanced skin cancer diagnosis and prognosis.Discover oncology · 2026Review
- Health economic evaluations of digital health technologies-a rapid review of applied methods.Frontiers in digital health · 2026Review
- Transparency of medical artificial intelligence systems.Nature reviews bioengineering · 2026Article
- Revolutionizing gastrointestinal cancer research with artificial intelligence: From precision patient stratification to real-world evidence.World journal of gastrointestinal oncology · 2025Review
- Planet-wide performance of a skin disease AI algorithm validated in Korea.NPJ digital medicine · 2025Article
- Review
- Teledermatology vs. Face-to-Face Dermatology for the Diagnosis of Melanoma: A Systematic Review.Cancers · 2025Review
- Artificial Intelligence in Aesthetic Medicine: Applications, Challenges, and Future Directions.Journal of cosmetic dermatology · 2025Review
- Mobile applications for skin cancer detection are vulnerable to physical camera-based adversarial attacks.Scientific reports · 2025Article
- Hallmarks of artificial intelligence contributions to precision oncology.Nature cancer · 2025Review
- Integrating artificial intelligence with smartphone-based imaging for cancer detection in vivo.Biosensors & bioelectronics · 2025Review
- Patient Consent and The Right to Notice and Explanation of AI Systems Used in Health Care.The American journal of bioethics : AJOB · 2025Article
- Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation.Frontiers in digital health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) based algorithms for classification of suspicious skin lesions have been implemented in mobile phone apps (mHealth), but their effect on healthcare systems is undocumented. In 2019, a large Dutch health insurance company offered 2.2 million adults free access to an mHealth app for skin cancer detection. To study the impact on dermatological healthcare consumption, we conducted a retrospective population-based pragmatic study. We matched 18,960 mHealth-users who completed at least one successful assessment with the app to 56,880 controls who did not use the app and calculated odds ratios (OR) to compare dermatological claims between both groups in the first year after granting free access. A short-term cost-effectiveness analysis was performed to determine the cost per additional detected (pre)malignancy. Here we report that mHealth-users had more claims for (pre)malignant skin lesions than controls (6.0% vs 4.6%, OR 1.3 (95% CI 1.2-1.4)) and also a more than threefold higher risk of claims for benign skin tumors and nevi (5.9% vs 1.7%, OR 3.7 (95% CI 3.4-4.1)). The costs of detecting one additional (pre)malignant skin lesion with the app compared to the current standard of care were €2567. Based on these results, AI in mHealth appears to have a positive impact on detecting more cutaneous (pre)malignancies, but this should be balanced against the for now stronger increase in care consumption for benign skin tumors and nevi.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.