ArticleCancers2022
Over-Detection of Melanoma-Suspect Lesions by a CE-Certified Smartphone App: Performance in Comparison to Dermatologists, 2D and 3D Convolutional Neural Networks in a Prospective Data Set of 1204 Pigmented Skin Lesions Involving Patients' Perception.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
22 citing papers in PubMed, 4 syntheses or guidelines pooled it, 52 citations in OpenAlex.
- Implementation of Total Body Photography for Skin Cancer Early Detection: A Systematic Review.International journal of dermatology · 2026Pooled it
- Prospective Evidence on Artificial Intelligence-Assisted Melanoma Diagnostics: A Systematic Review and Meta-Analysis.JAMA dermatology · 2026Pooled it
- Diagnostic Accuracy of Novel Optical Imaging Techniques for Melanoma Detection: A Systematic Review and Meta-Analysis.International journal of dermatology · 2025Pooled it
- Artificial intelligence for skin cancer detection and classification for clinical environment: a systematic review.Frontiers in medicine · 2023Pooled it
- Comparative Expert Evaluation of Multimodal Large Language Models for Pediatric Rash Diagnosis: Clinical Utility, Safety, Information Quality, and Readability.Children (Basel, Switzerland) · 2026Article
- Multimodal artificial intelligence for enhanced skin cancer diagnosis and prognosis.Discover oncology · 2026Review
- 3D Total Body Photography as a Promising Innovation for Early Skin Cancer Detection: Scoping Review.JMIR dermatology · 2025Article
- Teledermatology vs. Face-to-Face Dermatology for the Diagnosis of Melanoma: A Systematic Review.Cancers · 2025Review
- Advancements in Diagnosis of Neoplastic and Inflammatory Skin Diseases: Old and Emerging Approaches.Diagnostics (Basel, Switzerland) · 2025Review
- Assessment of a Smartphone-Based Neural Network Application for the Risk Assessment of Skin Lesions under Real-World Conditions.Dermatology practical & conceptual · 2025Article
- Review of Non-Invasive Imaging Technologies for Cutaneous Melanoma.Biosensors · 2025Review
- Integrating artificial intelligence with smartphone-based imaging for cancer detection in vivo.Biosensors & bioelectronics · 2025Review
- Biomimetic Materials for Skin Tissue Regeneration and Electronic Skin.Biomimetics (Basel, Switzerland) · 2024Review
- Human-AI interaction in skin cancer diagnosis: a systematic review and meta-analysis.NPJ digital medicine · 2024Review
- Review
- Recent Research Trends against Skin Carcinoma - An Overview.Current pharmaceutical design · 2024Review
- Artificial intelligence and skin cancer.Frontiers in medicine · 2024Review
- Recent Advances in Melanoma Diagnosis and Prognosis Using Machine Learning Methods.Current oncology reports · 2023Review
- Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The exponential increase in algorithm-based mobile health (mHealth) applications (apps) for melanoma screening is a reaction to a growing market. However, the performance of available apps remains to be investigated. In this prospective study, we investigated the diagnostic accuracy of a class 1 CE-certified smartphone app in melanoma risk stratification and its patient and dermatologist satisfaction. Pigmented skin lesions ≥ 3 mm and any suspicious smaller lesions were assessed by the smartphone app SkinVision
Indexed as
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.