Evidence map›Paper›PMID 36760363›Full record

ReviewFrontiers in cell and developmental biology2023

Research progress and application of artificial intelligence in thyroid associated ophthalmopathy.

Jiale Diao, Xinxin Chen, Ya Shen, Jian Li, Yuqing Chen, Linfeng He, Sainan Chen, Pei Mou, Xiaoye Ma, Ruili Wei

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.8field-weighted citation impact, top 7% 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

4 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

10 authors at 2 institutions in 1 country.

Jiale DiaoDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Xinxin ChenDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Ya ShenDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Jian LiDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Yuqing ChenDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Linfeng HeDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Sainan ChenDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Pei MouDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Xiaoye MaDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Ruili WeiDepartment of Ophthalmology, Changzheng Hospital of Naval Medicine University, Shanghai, China.
Second Military Medical University · CNShanghai Changzheng Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thyroid-associated ophthalmopathy (TAO) is a complicated orbitopathy related to dysthyroid, which severely destroys the facial appearance and life quality without medical interference. The diagnosis and management of thyroid-associated ophthalmopathy are extremely intricate, as the number of professional ophthalmologists is limited and inadequate compared with the number of patients. Nowadays, medical applications based on artificial intelligence (AI) algorithms have been developed, which have proved effective in screening many chronic eye diseases. The advanced characteristics of automated artificial intelligence devices, such as rapidity, portability, and multi-platform compatibility, have led to significant progress in the early diagnosis and elaborate evaluation of these diseases in clinic. This study aimed to provide an overview of recent artificial intelligence applications in clinical diagnosis, activity and severity grading, and prediction of therapeutic outcomes in thyroid-associated ophthalmopathy. It also discussed the current challenges and future prospects of the development of artificial intelligence applications in treating thyroid-associated ophthalmopathy.

Indexed as

artificial intelligenceautomated diagnosisdeep learningfacial imagesthyroid-associated ophthalmopathy

Identifiers

PMID36760363
PMCPMC9903073
OpenAlexW4319812768

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.