Evidence map›Paper›PMID 41625050›Full record

ArticleCureus2026

Current and Future Applications of Artificial Intelligence in Clinical Genetics.

Janet Lawrence

Abstract readEditorial
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Janet LawrenceMedical Education, Great Western Hospital, Swindon, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial Intelligence (AI) is transforming medicine, and its influence on clinical genetics cannot be ignored. From variant analysis and diagnostic interpretation to predictive and prognostic medicine, AI is improving the efficacy of genetic and genomic medicine using machine learning and deep learning systems to process large sequences of genomic data. This editorial explores current applications, highlights emerging advances, and discusses briefly the potential trajectory of AI in clinical genetics and our role to play as healthcare professionals. It also touches on the ethical limitations of AI in medicine.

Indexed as

artificial intelligenceclinical geneticsgenomicsmachine learningprecision medicinepreventive medicine

Identifiers

PMID41625050
PMCPMC12860534

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.