Evidence map›Paper›PMID 34712308›Full record

ArticlePakistan journal of medical sciences2021

Efficacy of liver cancer microwave ablation through ultrasonic image guidance under deep migration feature algorithm.

Changkong Ye, Wenyan Zhang, Zijuan Pang, Wei Wang

Open access · goldAbstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 54% 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

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

4 authors at 1 institution in 1 country.

Changkong YeChangkong Ye, Bachelor's Degrees. Department of Ultrasound, Beihai people's Hospital, Beihai 536000, China.
Wenyan ZhangWenyan Zhang, Bachelor's Degrees. Department of Ultrasound, Beihai people's Hospital, Beihai 536000, China.
Zijuan PangZijuan Pang, Master of Medicine. Department of Oncology, Beihai people's Hospital, Beihai 536000, China.
Wei WangWei Wang, Bachelor's Degrees. Department of Oncology, Beihai people's Hospital, Beihai 536000, China.
Beihai People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the therapeutic effects of ultrasound-guided microwave ablation and radio frequency ablation for liver cancer patients.

methodsSeventy-eight patients with microwave ablation were rolled into the experimental group and 56 patients with radio frequency ablation were in the control group. This study was conducted from March 1, 2019 to June 30, 2020 in our hospital. Based on Convolutional Neural Networks (CNN) and Migration feature (MF), a new ultrasound image diagnosis algorithm CNNMF was constructed, which was compared with AdaBoost and PCA-BP based on Principal component analysis (PCA) and back propagation (BP), and the accuracy (Acc), specificity (Spe), sensitivity (Sen), and F1 values of the three algorithms were calculated. Then, the CNNMF algorithm was applied to the ultrasonic image diagnosis of the two patients, and the postoperative ablation points, complications and ablation time were recorded.

resultsThe Acc (96.31%), Spe (89.07%), Sen (91.26%), and F1 value (0.79%) of the CNNMF algorithm were obviously larger than the AdaBoost and the PCA-BP algorithms (P< 0.05); in contrast with the control group. The number of ablation points in the experimental group was obviously larger, and the ablation time was obviously shorter (P<0.05); the experimental group had one case of liver abscess and two cases of wound pain after surgery, which were both obviously less than the control group (four cases; five cases) (P<0.05).

conclusionIn contrast with traditional algorithms, the CNNMF algorithm has better diagnostic performance for liver cancer ultrasound images. In contrast with radio frequency ablation, microwave ablation has better ablation effects for liver cancer tumors, and can reduce the incidence of postoperative complications in patients, which is safe and feasible.

Indexed as

CNNLiver cancerMFMicrowave ablationRadio frequency ablation

Identifiers

PMID34712308
PMCPMC8520357
OpenAlexW3191281996

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.