ArticleOrphanet journal of rare diseases2020
Diagnosis support systems for rare diseases: a scoping review.
Article in Orphanet journal of rare diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 2 of them syntheses that pooled it.
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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
46 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of studies that estimated the burden of chronic non-communicable rare diseases using disability-adjusted life years.Orphanet journal of rare diseases · 2024Pooled it
- [Short paths to diagnosis with artificial intelligence: systematic literature review on diagnostic decision support systems].Schmerz (Berlin, Germany) · 2024Pooled it
- Synthetic Echocardiograms from Diffusion Models in Rare Cardiovascular Disease.medRxiv : the preprint server for health sciences · 2026Article
- Rare-Disease Diagnosis on the ZebraMap Multimodal Case Report Dataset: A Hybrid Pipeline with Grounded Explainability.Sensors (Basel, Switzerland) · 2026Article
- ZebraMap: A Multimodal Rare Disease Knowledge Map with Automated Data Aggregation & LLM-Enriched Information Extraction Pipeline.Diagnostics (Basel, Switzerland) · 2025Article
- Identifying Parameters Associated with Delayed Diagnosis in Thrombotic Antiphospholipid Syndrome: Data from China Prospective APS Cohort.Advances in therapy · 2025Article
- Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records.Scientific reports · 2025Article
- Performance of ChatGPT-4o and Four Open-Source Large Language Models in Generating Diagnoses Based on China's Rare Disease Catalog: Comparative Study.Journal of medical Internet research · 2025Article
- Comparative analysis of large language models and traditional diagnostic decision support systems for rare rheumatic disease identification.EULAR rheumatology open · 2025Article
- Applying artificial intelligence to rare diseases: a literature review highlighting lessons from Fabry disease.Orphanet journal of rare diseases · 2025Review
- Rising to the Challenge of Rare Diagnoses.Journal of general internal medicine · 2025Article
- Improving musculoskeletal care with AI enhanced triage through data driven screening of referral letters.NPJ digital medicine · 2025Article
- Assessing the Utility of a Patient-Facing Diagnostic Tool Among Individuals With Hypermobile Ehlers-Danlos Syndrome: Focus Group Study.JMIR formative research · 2024Article
- Objectivizing issues in the diagnosis of complex rare diseases: lessons learned from testing existing diagnosis support systems on ciliopathies.BMC medical informatics and decision making · 2024Article
- [Rare diseases in a medical genetics service of population with social security].Revista medica del Instituto Mexicano del Seguro Social · 2024Article
- Loss of opportunities in the diagnosis and treatment of primary obstetric antiphospholipid syndrome (POAPS): from theory to reality.Clinical rheumatology · 2024Article
- Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening.Orphanet journal of rare diseases · 2024Article
- Learning to Make Rare and Complex Diagnoses With Generative AI Assistance: Qualitative Study of Popular Large Language Models.JMIR medical education · 2024Article
- Performance and clinical utility of a new supervised machine-learning pipeline in detecting rare ciliopathy patients based on deep phenotyping from electronic health records and semantic similarity.Orphanet journal of rare diseases · 2024Article
- A review of model evaluation metrics for machine learning in genetics and genomics.Frontiers in bioinformatics · 2024Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionRare diseases affect approximately 350 million people worldwide. Delayed diagnosis is frequent due to lack of knowledge of most clinicians and a small number of expert centers. Consequently, computerized diagnosis support systems have been developed to address these issues, with many relying on rare disease expertise and taking advantage of the increasing volume of generated and accessible health-related data. Our objective is to perform a review of all initiatives aiming to support the diagnosis of rare diseases.
methodsA scoping review was conducted based on methods proposed by Arksey and O'Malley. A charting form for relevant study analysis was developed and used to categorize data.
resultsSixty-eight studies were retained at the end of the charting process. Diagnosis targets varied from 1 rare disease to all rare diseases. Material used for diagnosis support consisted mostly of phenotype concepts, images or fluids. Fifty-seven percent of the studies used expert knowledge. Two-thirds of the studies relied on machine learning algorithms, and one-third used simple similarities. Manual algorithms were encountered as well. Most of the studies presented satisfying performance of evaluation by comparison with references or with external validation. Fourteen studies provided online tools, most of which aimed to support the diagnosis of all rare diseases by considering queries based on phenotype concepts.
conclusionNumerous solutions relying on different materials and use of various methodologies are emerging with satisfying preliminary results. However, the variability of approaches and evaluation processes complicates the comparison of results. Efforts should be made to adequately validate these tools and guarantee reproducibility and explicability.
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