Evidence map›Paper›PMID 42499774›Full record

ReviewPediatric investigation2026

Applications and prospects of artificial intelligence and digital medicine in pediatric nasal skull base tumors.

Xiuping Wu, Jing Wei, Chen Liu, Pengpeng Wang, Wentong Ge, Yang Han

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Pediatric investigation, 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

6 authors.

Xiuping WuDepartment of Otolaryngology, Head and Neck Surgery Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China.
Jing WeiClinical Research Center Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China.
Chen LiuDepartment of Otolaryngology, Head and Neck Surgery Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China.
Pengpeng WangDepartment of Otolaryngology, Head and Neck Surgery Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China.ORCID https://orcid.org/0000-0001-5694-1780
Wentong GeDepartment of Otolaryngology, Head and Neck Surgery Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China.
Yang HanDepartment of Otolaryngology, Head and Neck Surgery Beijing Children's Hospital, Capital Medical University, National Center for Children's Health Beijing China.ORCID https://orcid.org/0000-0002-4802-2992

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pediatric nasal skull base tumors are rare and difficult to diagnose early due to their deep anatomical location and children's limited ability to describe symptoms. When the tumors progress to advanced stages, nonspecific symptoms such as nasal congestion, nosebleeds, and facial swelling are easily confused with sinusitis or trauma, complicating diagnosis and treatment. Moreover, the special tumor anatomical location and the narrow nasal cavity in children increase the risk of tumor involvement with the surrounding structures. Given children's longer life expectancy and higher postoperative quality of life demands, personalized treatment and comprehensive medical management are essential. Advances in artificial intelligence (AI) and digital medicine have played an important role in early diagnosis, multidisciplinary treatment, prognosis assessment, and follow-up. However, despite the widespread use of emerging AI-related technologies, their application in pediatric nasal skull base tumors remains limited. This review discusses the potential applications of AI and digital medicine in the whole-process medical management of these tumors, including diagnosis, treatment, prognosis, and follow-up, along with current challenges.

Indexed as

Artificial intelligenceDigital medicineNasal skull base tumorsPediatricWhole‐process medical management model

Identifiers

PMID42499774
PMCPMC13398825

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.