ReviewFrontiers in medicine2020
Artificial Intelligence Applications in Dermatology: Where Do We Stand?
Review in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 45 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.
Using Artificial Intelligence as a Diagnostic Decision Support Tool to Help the Diagnosis of Skin Disease in Primary Healthcare in Catalonia
Development of an AI-Assisted Diagnostic Tool for Mycosis Fungoides and Other Cutaneous Lymphoproliferative Diseases Using Microscopic Image Analysis: A Training and Validation Study
Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advancements and challenges of artificial intelligence in dermatology: a review of applications and perspectives in China.Frontiers in digital health · 2025Pooled it
- AI-Assisted Quantitative Reflectance Confocal Microscopy Reveals Modulation of Senescence-Associated Epidermal Morphometric Features by a Topical TGF-β Mimetic, XEP™-716 Miniprotein™.Dermatology and therapy · 2026Article
- Advancing dermatology patients' quality of life through digital health innovations: a comprehensive systematic review.NPJ digital medicine · 2026Article
- Physicians' perceptions and attitudes on artificial intelligence in hospital management: a qualitative study.BMC health services research · 2025Article
- Current Trends and Future Directions of Digital Pathology and Artificial Intelligence in Dermatopathology: A Scientometric-Based Review.Diagnostics (Basel, Switzerland) · 2025Review
- Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives.Medical sciences (Basel, Switzerland) · 2025Review
- AI-driven healthcare: Fairness in AI healthcare: A survey.PLOS digital health · 2025Review
- A Review: Causes, Consequences, and Management Strategies of Facial Overfilling.Clinical, cosmetic and investigational dermatology · 2025Review
- Design and development of a machine-learning-driven opioid overdose risk prediction tool integrated in electronic health records in primary care settings.Bioelectronic medicine · 2024Article
- AI in Psoriatic Disease: Scoping Review.JMIR dermatology · 2024Article
- Assessing the Impact of ChatGPT in Dermatology: A Comprehensive Rapid Review.Journal of clinical medicine · 2024Review
- Claude 3 Opus and ChatGPT With GPT-4 in Dermoscopic Image Analysis for Melanoma Diagnosis: Comparative Performance Analysis.JMIR medical informatics · 2024Article
- Automated Machine Learning (AutoML) for the Diagnosis of Melanoma Skin Lesions From Consumer-Grade Camera Photos.Cureus · 2024Article
- A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare.Cureus · 2023Review
- Exploring the potential of artificial intelligence in improving skin lesion diagnosis in primary care.Scientific reports · 2023Article
- Analyzing the Predictability of an Artificial Intelligence App (Tibot) in the Diagnosis of Dermatological Conditions: A Cross-sectional Study.JMIR dermatology · 2023Article
- Deep Learning in Dermatology: A Systematic Review of Current Approaches, Outcomes, and Limitations.JID innovations : skin science from molecules to population health · 2023Review
- Principles, applications, and future of artificial intelligence in dermatology.Frontiers in medicine · 2023Review
- Machine Learning in Cardiology: A Potential Real-World Solution in Low- and Middle-Income Countries.Journal of multidisciplinary healthcare · 2023Review
- Artificial Intelligence in Dermatology Image Analysis: Current Developments and Future Trends.Journal of clinical medicine · 2022Review
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
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has become a progressively prevalent Research Topic in medicine and is increasingly being applied to dermatology. There is a need to understand this technology's progress to help guide and shape the future for medical care providers and recipients. We reviewed the literature to evaluate the types of publications on the subject, the specific dermatological topics addressed by AI, and the most challenging barriers to its implementation. A substantial number of original articles and commentaries have been published to date and only few detailed reviews exist. Most AI applications focus on differentiating between benign and malignant skin lesions, however; others exist pertaining to ulcers, inflammatory skin diseases, allergen exposure, dermatopathology, and gene expression profiling. Applications commonly analyze and classify images, however, other tools such as risk assessment calculators are becoming increasingly available. Although many applications are technologically feasible, important implementation barriers have been identified including systematic biases, difficulty of standardization, interpretability, and acceptance by physicians and patients alike. This review provides insight into future research needs and possibilities. There is a strong need for clinical investigation in dermatology providing evidence of success overcoming the identified barriers. With these research goals in mind, an appropriate role for AI in dermatology may be achieved in not so distant future.
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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.