ReviewEuropean journal of human genetics : EJHG2025
Artificial intelligence in clinical genetics.
Review in European journal of human genetics : EJHG, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on the generative AI applications in human medical genetics.Frontiers in genetics · 2025Pooled it
- Artificial Intelligence in Clinical Genetics: Current Applications and Challenges.Indian journal of pediatrics · 2026Review
- Trust, mistrust, and the promise of AI in genomics for African populations.American journal of human genetics · 2026Review
- Improving Polygenic Risk Prediction for Atherosclerotic Cardiovascular Disease in East Asian Populations.JACC. Asia · 2026Review
- Disparate language and model effects on AI-based translation and recognition of genetic conditions.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Why patient organizations are important to improve care for people with Lynch syndrome.Familial cancer · 2026Article
- Multidisciplinary blinded randomized expert evaluation of large language models for clinical diagnosis and management.Communications medicine · 2026Article
- Genetic analysis of neurodegenerative diseases.The Journal of clinical investigation · 2026Review
- Harnessing artificial intelligence to advance CRISPR-based genome editing technologies.Nature reviews. Genetics · 2026Review
- Artificial Intelligence agents for biological research: a survey.Briefings in bioinformatics · 2026Article
- Rethinking scale in AI-driven genomic medicine - The role of small biobanks.Frontiers in genetics · 2026Article
- Performance and limitations of four large language models in genetic counseling for thalassemia.Frontiers in digital health · 2026Article
- Toward personalized medicine in AD/ADRD through genetic-exposome dementia risk assessments.NPJ dementia · 2026Review
- Article
- Artificial intelligence in head and neck cancer: a bibliometric and visualization analysis (1995-2025).Discover oncology · 2025Article
- Bridging Andrology and Oncology: Prognostic Indicators of Cancer Among Infertile Men.Current issues in molecular biology · 2025Review
- Perspectives on the Current and Future State of Artificial Intelligence in Medical Genetics.American journal of medical genetics. Part A · 2025Review
- NGS Approaches in Clinical Diagnostics: From Workflow to Disease-Specific Applications.International journal of molecular sciences · 2025Review
- The quest for a complete understanding of the human genome.Genome medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Artificial intelligence (AI) has been growing more powerful and accessible, and will increasingly impact many areas, including virtually all aspects of medicine and biomedical research. This review focuses on previous, current, and especially emerging applications of AI in clinical genetics. Topics covered include a brief explanation of different general categories of AI, including machine learning, deep learning, and generative AI. After introductory explanations and examples, the review discusses AI in clinical genetics in three main categories: clinical diagnostics; management and therapeutics; clinical support. The review concludes with short, medium, and long-term predictions about the ways that AI may affect the field of clinical genetics. Overall, while the precise speed at which AI will continue to change clinical genetics is unclear, as are the overall ramifications for patients, families, clinicians, researchers, and others, it is likely that AI will result in dramatic evolution in clinical genetics. It will be important for all those involved in clinical genetics to prepare accordingly in order to minimize the risks and maximize benefits related to the use of AI in the field.
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.