Artificial Intelligence in Clinical Genetics: Current Applications and Challenges.
AI is accelerating rare disease diagnosis by matching patient symptoms to genes and predicting which genetic changes cause disease, reducing the diagnostic odyssey.
This review systematically covers current AI applications transforming clinical genetics practice for rare disease diagnosis, including AI-powered phenotype–genotype matching, variant interpretation, and integration of multiomics and long-read sequencing data to resolve previously undiagnosed patients. The review identifies key implementation challenges including interpretability requirements, dataset diversity gaps, and the regulatory/clinical integration hurdles that must be addressed for AI clinical genetics tools to reach their full potential for reducing the diagnostic odyssey in rare diseases.
What the study was
- Study design
- Narrative review
- Population
- Rare disease patients undergoing genetic workup; clinical genetics practice
- Category
- Diagnostics
- Maturity
- Exploratory
- Journal
- Indian journal of pediatrics
Why it surfaced
Timely review of AI's expanding role in rare disease clinical genetics; AI-powered variant interpretation and phenotype matching are near-term implementable tools with direct impact on diagnostic yield and rare disease patient timelines.
A plain-language summary of published research — not medical advice. Talk to a clinician about your own care.