Evidence map›Paper›PMID 34867113›Full record

Trial reportContrast media & molecular imaging2021

Analysis of Lung Imaging Intelligent Diagnosis System for Nursing Intervention of Lung Cancer Patients' Quality of Life.

Ruxia Guo, Hui Wang

Open access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Contrast media & molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 34% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

2 authors at 1 institution in 1 country.

Ruxia GuoOncology Department Zhejiang Hospital, Hangzhou, Zhejiang 310030, China.ORCID 0000-0002-2484-8327
Hui WangOncology Department Zhejiang Hospital, Hangzhou, Zhejiang 310030, China.ORCID 0000-0002-3609-522X
Zhejiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to explore the influence of intelligent imaging diagnosis systems on comprehensive nursing intervention for patients with late-stage lung cancer, the system uses ITK and VTK toolkit to realize image reading, display, image marking, and interactive functions. The optimal threshold method and regional connectivity algorithm were used to segment the lung region, and then, the cavity filling algorithm and repair algorithm were used to repair the lung region. A variable ring filter was used to detect suspected shadows in the lungs. Finally, the classifier proposed in this paper is used to classify benign and malignant. The system has good sensitivity by detecting the images of real patients. 100 patients with advanced lung cancer were randomly divided into control group and nursing intervention group 50 cases each. Patients in the control group received routine radiotherapy and chemotherapy and routine nursing intervention. Patients in the nursing intervention group were given comprehensive nursing intervention on the basis of routine intervention in the control group for 2 consecutive months. Pittsburgh sleep quality index, pain degree, quality of life, and complications after intervention were compared between the 2 groups before and after intervention. The experimental results showed that the sleep quality, pain degree, quality of life, and complications in 2 groups were significantly improved after intervention (

Indexed as

Lung NeoplasmsQuality of LifeHumansLung

Identifiers

PMID34867113
PMCPMC8608502
OpenAlexW3213753641

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.