ReviewFrontiers in medicine2024
Artificial intelligence and skin cancer.
Review in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis 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
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep Learning Algorithms in the Diagnosis of Basal Cell Carcinoma Using Dermatoscopy: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Automated Skin Lesion and Cancer Detection Using Computer Vision: A Comprehensive Review.Bioengineering (Basel, Switzerland) · 2026Review
- When AI and Experts Agree on Error: Intrinsic Ambiguity in Dermatoscopic Images.Journal of imaging · 2026Article
- Artificial intelligence in three-dimensional total-body photography for skin cancer surveillance.Frontiers in medicine · 2026Review
- From theory to therapy: integrating artificial intelligence for transformative healthcare innovation.Health systems (Basingstoke, England) · 2026Article
- Legal and ethical reflections on the use of artificial intelligence in the diagnosis and treatment of cancer: who assumes responsibility?Frontiers in artificial intelligence · 2026Article
- Clinical evaluation of large language model recommendations in melanoma: comparison with multidisciplinary tumor board decisions in a real-world cohort.Frontiers in oncology · 2026Article
- Diagnostic accuracy of machine-learning-based image analysis for early detection of Kaposi sarcoma in people living with HIV.Frontiers in artificial intelligence · 2026Review
- Review
- Clinical Application of Vision Transformers for Melanoma Classification: A Multi-Dataset Evaluation Study.Cancers · 2025Article
- The Current State and Future Prospects for Artificial Intelligence in Dermatology.Dermatologic clinics · 2025Review
- Current Trends and Future Directions of Digital Pathology and Artificial Intelligence in Dermatopathology: A Scientometric-Based Review.Diagnostics (Basel, Switzerland) · 2025Review
- Article
- Deep Hair Phenomics: Implications in Endocrinology, Development, and Aging.The Journal of investigative dermatology · 2025Article
- Indirect Impact of Pandemic on the Diagnosis of New Primary Melanoma: A Retrospective, Multicenter Study.Journal of clinical medicine · 2025Article
- Integrating AI and Assistive Technologies in Healthcare: Insights from a Narrative Review of Reviews.Healthcare (Basel, Switzerland) · 2025Review
- Using the power of artificial intelligence to improve the diagnosis and management of nonmelanoma skin cancer.Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences · 2025Review
- Skin Cancer: Epidemiology, Screening and Clinical Features of Acral Lentiginous Melanoma (ALM), MelanomaJournal of Cancer · 2025Review
- Enhancing dermatological diagnosis for differentiating actinic from seborrheic keratosis using deep learning model.Frontiers in medicine · 2025Article
- Artificial intelligence in systemic diagnostics: Applications in psychiatry, cardiology, dermatology and oral pathology.Bioinformation · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Artificial intelligence is poised to rapidly reshape many fields, including that of skin cancer screening and diagnosis, both as a disruptive and assistive technology. Together with the collection and availability of large medical data sets, artificial intelligence will become a powerful tool that can be leveraged by physicians in their diagnoses and treatment plans for patients. This comprehensive review focuses on current progress toward AI applications for patients, primary care providers, dermatologists, and dermatopathologists, explores the diverse applications of image and molecular processing for skin cancer, and highlights AI's potential for patient self-screening and improving diagnostic accuracy for non-dermatologists. We additionally delve into the challenges and barriers to clinical implementation, paths forward for implementation and areas of active research.
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.