ArticleAfrican health sciences2023
Using artificial intelligence on dermatology conditions in Uganda: a case for diversity in training data sets for machine learning.
Article in African health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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
41 citing papers in PubMed, 68 citations in OpenAlex.
- Demographic Reporting and the Absence of Hispanic/Latino Representation in Dermatology Artificial Intelligence: A Scoping Review.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2026Article
- Artificial intelligence in dermatology: A literature review of current evidence and clinical implementation.JID innovations : skin science from molecules to population health · 2026Review
- Artificial intelligence in inflammatory bowel disease: bridging innovation, implementation and impact.Nature reviews. Gastroenterology & hepatology · 2026Review
- Artificial Intelligence-Based Diagnosis of Kaposi Sarcoma Using Digital Photographs in Dark-Skinned Patients in Uganda.JCO global oncology · 2026Article
- Transforming Public Health Practice with Artificial Intelligence: A Framework-Driven Approach.Healthcare (Basel, Switzerland) · 2026Article
- Clinical Features and Risk Factors of Dermatitis Cruris Pustulosa et Atrophicans in Southwestern Uganda: A Cross-Sectional Study.Clinical, cosmetic and investigational dermatology · 2026Article
- A Comprehensive Approach to Responsible AI Development and Deployment.Mayo Clinic proceedings. Digital health · 2025Review
- Review
- Diagnostic performance of artificial intelligence for dermatological conditions: a systematic review focused on low- and middle-income countries to address resource constraints and improve access to specialist care.International journal of emergency medicine · 2025Review
- Artificial Intelligence (AI) and Emergency Medicine: Balancing Opportunities and Challenges.JMIR medical informatics · 2025Review
- Representation of Demographics in Otolaryngology by Artificial Intelligence Text-to-Image Platforms.Laryngoscope investigative otolaryngology · 2025Article
- Rethinking the use of population descriptors in dermatology trials and beyond: disentangling race and ethnicity from skin color.Archives of dermatological research · 2025Article
- Improving medical machine learning models with generative balancing for equity and excellence.NPJ digital medicine · 2025Article
- The Data Artifacts Glossary: a community-based repository for bias on health datasets.Journal of biomedical science · 2025Article
- Understanding artificial intelligence in critical care: opportunities, risks, and practical applications.Critical care science · 2025Review
- The Impact of Artificial Intelligence on Cancer Diagnosis and Treatment: A Review.Cancer informatics · 2025Review
- Ethical data acquisition for LLMs and AI algorithms in healthcare.NPJ digital medicine · 2024Review
- Applications of ChatGPT in Heart Failure Prevention, Diagnosis, Management, and Research: A Narrative Review.Diagnostics (Basel, Switzerland) · 2024Review
- AI-Enhanced Healthcare: Not a new Paradigm for Informed Consent.Journal of bioethical inquiry · 2024Article
- The Sociodemographic Biases in Machine Learning Algorithms: A Biomedical Informatics Perspective.Life (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: In pursuit of applying universal non-biased Artificial Intelligence (AI) in healthcare, it is essential that data from different geographies are represented. Objective: To assess the diagnostic performance of an AI-powered dermatological algorithm called Skin Image Search on Fitzpatrick 6 skin type (dark skin) dermatological conditions. Methods: 123 dermatological images selected from a total of 173 images were retrospectively extracted from the electronic database of a Ugandan telehealth company, The Medical Concierge Group (TMCG) after getting their consent. Details of age, gender, and dermatological clinical diagnosis were analysed using R on R studio software to assess the diagnostic accuracy of the AI app along with disease diagnosis and body part. Predictability levels of the AI app were graded on a scale of 0 to 5, where 0- no prediction was made and 1-5 demonstrated a reduction incorrect diagnosis prediction rate of the AI. Results: 76 (62%) of the dermatological images were from females and 47 (38%) from males. Overall diagnostic accuracy of the AI app on black dermatological conditions was low at 17% (21 out of 123 predictable images) compared to 69.9% performance on Caucasian skin type as reported from the training results. There were varying predictability levels correctness i.e., 1-8.9%, 2-2.4%, 3-2.4%, 4-1.6%, 5-1.6% with performance along individual diagnosis highest with dermatitis (80%). Conclusion: There is need for diversity of image datasets used to train dermatology algorithms for AI applications to increase accuracy across skin types and geographies.
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.