Summary: This article examines AI enabled genomic decision support with an academic translational focus. It synthesizes variant interpretation pipelines, risk prediction models, and nursing education and counseling implications.

Genomic data increasingly inform risk stratification and medication selection. Nurses play a key role in collecting family history, educating patients, and coordinating genomic testing and follow up.

Technically systems integrate variant annotation, polygenic risk scores, and EHR phenotypes to generate actionable summaries. Explainability and provenance are critical. Validation requires clinical cohorts, concordance with geneticist review, and assessment of patient understanding and outcomes.

Guidance: Guidance: present concise, nurse friendly genomic summaries, include clear action items and referral triggers, provide training for genomic literacy, and ensure informed consent and data privacy.

Conclusion: AI genomic support can enhance personalized care when outputs are interpretable, validated, and paired with nursing education and genetic counseling pathways.

Final Summary: variant annotation; risk scores; explainable summaries; referral triggers; genomic literacy training

Useful Facts: precision medicine | genetics | nursing education

Related Topics: nursing;genomics Genomic outputs require expert validation; Explainability aids nurse communication; Polygenic scores need careful interpretation; Consent and privacy are paramount; Training improves nurse confidence