ArticleCancers2024
Clinical Utility of a Digital Dermoscopy Image-Based Artificial Intelligence Device in the Diagnosis and Management of Skin Cancer by Dermatologists.
Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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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
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- "First, do no harm" in the digital era: examining the practicality of the European Health Data Space proposal and ethical implications of artificial intelligence: A systematic literature review.BMC medical ethics · 2026Pooled it
- Multiple Basal Cell Carcinomas in a Long-Term Survivor of Childhood ALL and HSCT-A Call for Dermatologic Vigilance.Life (Basel, Switzerland) · 2025Review
- Translating Features to Findings: Deep Learning for Melanoma Subtype Prediction.Dermatopathology (Basel, Switzerland) · 2025Review
- [Artificial intelligence in total body photography, digital dermoscopy and high-resolution dermoscopy].Dermatologie (Heidelberg, Germany) · 2025Review
- Comparative Dermoscopic Analysis of Melanoma In Situ Versus Thin Invasive Melanoma Considering BRAF Mutational Status.Journal of clinical medicine · 2025Article
- Advancements in Diagnosis of Neoplastic and Inflammatory Skin Diseases: Old and Emerging Approaches.Diagnostics (Basel, Switzerland) · 2025Review
- Dermatoscopic Patterns in Mycosis Fungoides: Observations from a Case-Series Retrospective Analysis and a Review of the Literature.Diagnostics (Basel, Switzerland) · 2025Article
- Convergence of evolving artificial intelligence and machine learning techniques in precision oncology.NPJ digital medicine · 2025Article
- Clinical EvaluationIn vivo (Athens, Greece)Article
- AI-Assisted Dermatology in Provider Shortage Areas: A Systematic Review of Access and Wait Time Outcomes.The Journal of clinical and aesthetic dermatologyReview
- Advances in the noninvasive diagnosis of melanoma-40 years beyond the ABCDs.CA: a cancer journal for cliniciansReview
- Characteristic Clinical Features of Melanoma in Patients With Excised Skin Lesions.Cancer diagnosis & prognosisArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
26 authors.
Funding
Abstract
backgroundPatients with skin lesions suspicious for skin cancer or atypical melanocytic nevi of uncertain malignant potential often present to dermatologists, who may have variable dermoscopy triage clinical experience.
objectiveTo evaluate the clinical utility of a digital dermoscopy image-based artificial intelligence algorithm (DDI-AI device) on the diagnosis and management of skin cancers by dermatologists.
methodsThirty-six United States board-certified dermatologists evaluated 50 clinical images and 50 digital dermoscopy images of the same skin lesions (25 malignant and 25 benign), first without and then with knowledge of the DDI-AI device output. Participants indicated whether they thought the lesion was likely benign (unremarkable) or malignant (suspicious).
resultsThe management sensitivity of dermatologists using the DDI-AI device was 91.1%, compared to 84.3% with DDI, and 70.0% with clinical images. The management specificity was 71.0%, compared to 68.4% and 64.9%, respectively. The diagnostic sensitivity of dermatologists using the DDI-AI device was 86.1%, compared to 78.8% with DDI, and 63.4% with clinical images. Diagnostic specificity using the DDI-AI device increased to 80.7%, compared to 75.9% and 73.6%, respectively.
conclusionThe use of the DDI-AI device may quickly, safely, and effectively improve dermoscopy performance, skin cancer diagnosis, and management when used by dermatologists, independent of training and experience.
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