Evidence map›Paper›PMID 42572031›Full record

ReviewActa epileptologica2026

Clinical application of artificial intelligence technology in epilepsy.

Qi Ren, Yan Zhang, Xiaohong Deng, Meng Fu, Xia Li, Luyao Wang, Xianpeng Chen, Yu Yang, Jinfeng Zhang

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Acta epileptologica, 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

9 authors.

Qi Ren *Affiliated Baotou Clinical College of Inner Mongolia Medical University, Baotou, Inner Mongolia, 014040, People's Republic of China.
Yan Zhang *Affiliated Baotou Clinical College of Inner Mongolia Medical University, Baotou, Inner Mongolia, 014040, People's Republic of China.
Xiaohong DengDepartment of Neurology, Baotou Central Hospital, Baotou, Inner Mongolia, 014040, People's Republic of China.
Meng FuDepartment of Neurology, Baotou Central Hospital, Baotou, Inner Mongolia, 014040, People's Republic of China.
Xia LiDepartment of Neurology, Baotou Central Hospital, Baotou, Inner Mongolia, 014040, People's Republic of China.
Luyao WangDepartment of Neurology, Baotou Central Hospital, Baotou, Inner Mongolia, 014040, People's Republic of China.
Xianpeng ChenAffiliated Baotou Clinical College of Inner Mongolia Medical University, Baotou, Inner Mongolia, 014040, People's Republic of China.
Yu YangAffiliated Baotou Clinical College of Inner Mongolia Medical University, Baotou, Inner Mongolia, 014040, People's Republic of China.
Jinfeng ZhangAffiliated Baotou Clinical College of Inner Mongolia Medical University, Baotou, Inner Mongolia, 014040, People's Republic of China. rose790310@163.com.

Funding

the project of Joint Fund for Scientific Research of Public Hospitals of Inner Mongolia Academy of Medical Sciences 2024GLLH0468
6 · The paper itself

Abstract

Epilepsy is a prevalent neurological disorder, and its inherent complexity and significant interindividual variability pose substantial challenges for clinical diagnosis and treatment. Against this backdrop, the rapid development of artificial intelligence (AI) technology is driving a historic paradigm shift in the field of epilepsy diagnosis and management. This review analyses the application of AI in four core domains of epilepsy clinical practice: early diagnosis, accurate seizure prediction, individualized treatment, and long-term disease management. The primary objectives of this review are to delineate the current status of the clinical application of AI in epilepsy, clarify emerging future trends, and ultimately provide practical references and actionable insights for clinical practitioners.

Indexed as

Artificial intelligenceDeep learningElectroencephalographyEpilepsyMachine learningNeuroimaging

Identifiers

PMID42572031
PMCPMC13455378

What Socratic 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 Socratic graph.