Evidence map›Paper›PMID 35936360›Full record

ArticleComputational and mathematical methods in medicine2022

MRI Using Artificial Intelligence Algorithm to Evaluate Concurrent Chemoradiotherapy for Local Recurrence and Distant Metastasis of Cervical Squamous Cell Carcinoma.

Youyi Wu, Tingting Chen, Yiwei Huang, Yongchou Li, Xiaoyan Wang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 46% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Youyi WuDepartment of Oncology Radiotherapy, The Third Affiliated Hospital of Wenzhou Medical University (Ruian People's Hospital), Ruian, Wenzhou, 325200 Zhejiang, China.ORCID https://orcid.org/0000-0001-7804-225X
Tingting ChenDepartment of Oncology Radiotherapy, The Third Affiliated Hospital of Wenzhou Medical University (Ruian People's Hospital), Ruian, Wenzhou, 325200 Zhejiang, China.ORCID https://orcid.org/0000-0003-3473-3133
Yiwei HuangDepartment of Oncology Radiotherapy, The Third Affiliated Hospital of Wenzhou Medical University (Ruian People's Hospital), Ruian, Wenzhou, 325200 Zhejiang, China.ORCID https://orcid.org/0000-0003-2553-1054
Yongchou LiDepartment of Radiology and Imaging, The Third Affiliated Hospital of Wenzhou Medical University (Ruian People's Hospital), Ruian, Wenzhou, 325200 Zhejiang, China.ORCID https://orcid.org/0000-0001-8264-4122
Xiaoyan WangDepartment of Oncology Radiotherapy, The Third Affiliated Hospital of Wenzhou Medical University (Ruian People's Hospital), Ruian, Wenzhou, 325200 Zhejiang, China.ORCID https://orcid.org/0000-0001-6970-4688
Wenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to investigate the magnetic resonance imaging (MRI) features of patients with local recurrence and distant metastasis of cervical squamous cell carcinoma before and after concurrent chemoradiotherapy based on artificial intelligence algorithm. In this study, 100 patients with cervical squamous cell carcinoma with local recurrence and distant metastasis who underwent concurrent chemoradiotherapy were collected as the research subjects, and all underwent MRI multisequence imaging scans. At the same time, according to the evaluation criteria of solid tumor efficacy, patients with complete remission were classified into the effective group, and patients with partial remission, progressive disease, and stable disease were classified into the ineffective group. In addition, an image segmentation algorithm based on Balloon Snake model was proposed for MRI image processing, and simulation experiments were carried out. The results showed that the Dice coefficient of the proposed model segmentation of the reconstructed image was significantly higher than that of the level set model and the greedy algorithm, while the running time was the opposite (

Indexed as

Carcinoma, Squamous CellUterine Cervical NeoplasmsArtificial IntelligenceChemoradiotherapyFemaleHumansMagnetic Resonance Imaging

Identifiers

PMID35936360
PMCPMC9352503
OpenAlexW4288445686

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.