Evidence map›Paper›PMID 40980482›Full record

ArticleJournal of research in medical sciences : the official journal of Isfahan University of Medical Sciences2025

Generative artificial intelligence: In the search for new landscapes in basic and clinical nephrology.

Farnoush Kiyanpour, Ali Motahharynia, Marek Ostaszewski, Yousof Gheisari

Abstract read
In one paragraph

Article in Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences, 2025. 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

4 authors.

Farnoush KiyanpourDepartment of Advanced Medical Technology, Isfahan University of Medical Sciences, Isfahan, Iran.
Ali MotahharyniaRegenerative Medicine Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Marek OstaszewskiBioinformatics Core, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg.
Yousof GheisariRegenerative Medicine Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rise of systems biology has improved the understanding of complex disorders such as chronic kidney disease by providing predictive and comprehensive models. Despite the abundance of omics data, translation to clinical solutions remains a challenge. Artificial intelligence (AI), especially generative AI, promises to fill this gap through mining, integration, and processing of diverse and intricate raw data for the generation of actionable knowledge. Recently introduced AI tools have shown great potential in clinical nephrology for improved diagnosis and prognosis. This approach is also promising for the identification of novel therapeutic targets, repurposing of already approved drugs, and precision nephrology. The rapid advancement of this technology is definitely associated with critical ethical and legal concerns for which the scientific community needs to be prepared.

Indexed as

Artificial intelligencediabetic kidney diseasedrug repositioningdrug target identificationkidney diseases

Identifiers

PMID40980482
PMCPMC12445765

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.