ArticleHGG advances2022
Neural network classifiers for images of genetic conditions with cutaneous manifestations.
Article in HGG advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed.
- Artificial intelligence in genomic medicine: dispelling three myths.NPJ genomic medicine · 2026Article
- Perspectives on the Current and Future State of Artificial Intelligence in Medical Genetics.American journal of medical genetics. Part A · 2025Review
- Deep Learning Study of Alkaptonuria Spinal Disease Assesses Global and Regional Severity and Detects Occult Treatment Status.Journal of inherited metabolic disease · 2025Article
- Artificial intelligence in clinical genetics.European journal of human genetics : EJHG · 2025Review
- Approximating facial expression effects on diagnostic accuracy via generative AI in medical genetics.Bioinformatics (Oxford, England) · 2024Article
- Recognition of Genetic Conditions After Learning With Images Created Using Generative Artificial Intelligence.JAMA network open · 2024Article
- Comparison of clinical geneticist and computer visual attention in assessing genetic conditions.PLoS genetics · 2024Article
- AI in dermatology: a comprehensive review into skin cancer detection.PeerJ. Computer science · 2024Article
- Generative Methods for Pediatric Genetics Education.medRxiv : the preprint server for health sciences · 2023Article
- Scoping review and classification of deep learning in medical genetics.Genetics in medicine : official journal of the American College of Medical Genetics · 2022Article
- Neural Networks for Classification and Image Generation of Aging in Genetic Syndromes.Frontiers in genetics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Neural networks have shown strong potential in research and in healthcare. Mainly due to the need for large datasets, these applications have focused on common medical conditions, where more data are typically available. Leveraging publicly available data, we trained a neural network classifier on images of rare genetic conditions with skin findings. We used approximately 100 images per condition to classify 6 different genetic conditions. We analyzed both preprocessed images that were cropped to show only the skin lesions as well as more complex images showing features such as the entire body segment, the person, and/or the background. The classifier construction process included attribution methods to visualize which pixels were most important for computer-based classification. Our classifier was significantly more accurate than pediatricians or medical geneticists for both types of images and suggests steps for further research involving clinical scenarios and other applications.
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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.