Evidence map›Paper›PMID 36760995›Full record

ArticleFrontiers in genetics2023

Preliminary investigation of the diagnosis and gene function of deep learning PTPN11 gene mutation syndrome deafness.

Xionghui Wu, Min Huang, Weiqing Huang, Sijun Zhao, Jiang Xie, Guangliang Liu, Shuting Chang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 44% of its field
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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Clinical phenotypes and cochlear implant outcomes in patients with PTPN11-associated noonan spectrum disorders: Insights from a genetically screened cohort.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026
    Article
  2. Article
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

7 authors at 1 institution in 1 country.

Xionghui WuDepartment of Otorhinolaryngology Head and Neck Surgery, Hunan Children's Hospital, Changsha, Hunan, China.
Min HuangDepartment of Otorhinolaryngology Head and Neck Surgery, Hunan Children's Hospital, Changsha, Hunan, China.
Weiqing HuangDepartment of Neonatology, Hunan Children's Hospital, Changsha, Hunan, China.
Sijun ZhaoDepartment of Otorhinolaryngology Head and Neck Surgery, Hunan Children's Hospital, Changsha, Hunan, China.
Jiang XieDepartment of Otorhinolaryngology Head and Neck Surgery, Hunan Children's Hospital, Changsha, Hunan, China.
Guangliang LiuDepartment of Otorhinolaryngology Head and Neck Surgery, Hunan Children's Hospital, Changsha, Hunan, China.
Shuting ChangDepartment of Neonatology, Hunan Children's Hospital, Changsha, Hunan, China.
Hunan Children's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Syndromic deafness caused by PTPN11 gene mutation has gradually come into the public's view. In the past, many people did not understand its application mechanism and role and only focused on non-syndromic deafness, so the research on syndromic deafness is not in-depth and there is a large degree of lack of research in this area. In order to let the public know more about the diagnosis and gene function of deafness caused by PTPN11 gene mutation syndrome, this paper used deep learning technology to study the diagnosis and gene function of deafness caused by syndrome with the concept of intelligent medical treatment, and finally drew a feasible conclusion. This paper provided a theoretical and practical basis for the diagnosis of deafness caused by PTPN11 gene mutation syndrome and the study of gene function. This paper made a retrospective analysis of the clinical data of 85 deaf children who visited Hunan Children's Hospital,P.R. China from January 2020 to December 2021. The conclusion were as follows: Children aged 1-6 years old had multiple syndrome deafness, while children under 1 year old and children aged 6-12 years old had relatively low probability of complex deafness; girls were not easy to have comprehensive deafness, but there was no specific basis to prove that the occurrence of comprehensive deafness was necessarily related to gender; the hearing loss of patients with Noonan Syndrome was mainly characterized by moderate and severe damage and abnormal inner ear and auditory nerve; most of the mutation genes in children were located in Exon1 and Exon3, with a total probability of 57.65%. In the course of the experiment, it was found that deep learning was effective in the diagnosis of deafness with PTPN11 gene mutation syndrome. This technology could be applied to medical diagnosis to facilitate the diagnosis and treatment of more patients with deafness with syndrome. Intelligent medical treatment was also becoming a hot topic nowadays. By using this concept to analyze and study the pathological characteristics of deafness caused by PTPN11 gene mutation syndrome, it not only promoted patients to find diseases in time, but also helped doctors to diagnose and treat such diseases, which was of great significance to patients and doctors. The study of PTPN11 gene mutation syndrome deafness was also of great significance in genetics. The analysis of its genes not only enriched the gene pool, but also provided reference for future research.

Indexed as

deep learningdiagnosis and gene functionintelligent medicinePTPN11 gene mutationsyndrome deafness

Identifiers

PMID36760995
PMCPMC9907458
OpenAlexW4318045053

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.