ReviewClinical and translational science2023
Artificial intelligence in rare disease diagnosis and treatment.
Review in Clinical and translational science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 3 of them syntheses 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
63 citing papers in PubMed, 3 syntheses or guidelines pooled it, 134 citations in OpenAlex.
- Tissue and systemic inflammation in dystrophic epidermolysis bullosa: a systematic review and meta-analysis.Orphanet journal of rare diseases · 2025Pooled it
- Diagnostic models for sepsis-associated encephalopathy: a comprehensive systematic review and meta-analysis.Frontiers in neurology · 2025Pooled it
- Quantifying hope: an EU perspective of rare disease therapeutic space and market dynamics.Frontiers in public health · 2025Pooled it
- Systematic review of artificial intelligence and digital-automated tools for screening, diagnosis and characterisation of primary ciliary dyskinesia.ERJ open research · 2026Article
- Artificial Intelligence Competencies and Educational Needs Among ERNICA Members: Results of a Multinational Survey.European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie · 2026Article
- From Small Data to Big Decisions: How Clinical Pharmacology Shapes Rare Disease Development.Journal of clinical pharmacology · 2026Review
- Real-World Imaging Data: Opportunities and Challenges.JMIR medical informatics · 2026Article
- Patients' and Providers' Attitudes Toward Artificial Intelligence and Electronic Health Record Use in Deep Phenotyping and Rare-Disease Screening: An Empty Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
- Characterizing patients who benefit from mature medical AI models in real-world clinical applications.PLOS digital health · 2026Article
- Reimagining care of people living with rare diseases with artificial intelligence.PLoS medicine · 2026Article
- Privacy-by-Design with Federated Learning will drive future Rare Disease Research.Journal of neuromuscular diseases · 2026Review
- A clinically deployable deep learning model for automated stroke risk stratification in carotid atherosclerotic plaque.Frontiers in medicine · 2026Article
- Predicting wound healing outcomes: a comparative accuracy analysis of AI-driven indices and percent area reduction.BMJ digital health & AI · 2026Article
- ZebraMap: A Multimodal Rare Disease Knowledge Map with Automated Data Aggregation & LLM-Enriched Information Extraction Pipeline.Diagnostics (Basel, Switzerland) · 2025Article
- Co-creation process of an app for people with rare diseases - a citizen science approach.Orphanet journal of rare diseases · 2025Article
- Structured panendoscopy reports improve report completeness and documentation time.Scientific reports · 2025Article
- Argo Delphi consensus statement on red flags and clinical gateways towards rare disease diagnosis.Scientific reports · 2025Article
- Individualized Medicine in the Era of Artificial Intelligence.Mayo Clinic proceedings · 2025Review
- Evaluation of artificial ıntelligence use in ankylosing spondylitis with ChatGPT-4: patient and physician perspectives.Clinical rheumatology · 2025Article
- Workflow analysis and evaluation of a next-generation phenotyping tool: A qualitative study of Face2Gene.European journal of human genetics : EJHG · 2025Article
3 more citing papers are in PubMed but not listed here.
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 at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) utilization in health care has grown over the past few years. It also has demonstrated potential in improving the efficiency of diagnosis and treatment. Some types of AI, such as machine learning, allow for the efficient analysis of vast datasets, identifying patterns, and generating key insights. Predictions can then be made for medical diagnosis and personalized treatment recommendations. The use of AI can bypass some conventional limitations associated with rare diseases. Namely, it can optimize traditional randomized control trials, and may eventually reduce costs for drug research and development. Recent advancements have enabled researchers to train models based on large datasets and then fine-tune these models on smaller datasets typically associated with rare diseases. In this mini-review, we discuss recent advancements in AI and how AI can be applied to streamline rare disease diagnosis and optimize treatment.
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.