Evidence map›Paper›PMID 36741503›Full record

ArticleFrontiers in neurorobotics2023

Effect analysis of neural network robot system in music relaxation training to alleviate adverse reactions of chemotherapy in patients with breast cancer.

Yue Teng, Jinlei Bao, Yinfeng Li, Haichun Ye

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurorobotics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 3 institutions in 2 countries.

Yue TengCollege of Human and Health Sciences, Swansea University, Swansea, United Kingdom.
Jinlei BaoCollege of Nursing, Shandong Xiehe University, Jinan, Shandong, China.
Yinfeng LiSchool of Medicine, Sichuan Cancer Hospital and Institute, Sichuan Cancer Centre, University of Electronic Science and Technology of China, Chengdu, China.
Haichun YeDepartment of Geriatric Services and Management, School of Humanities Education, Ningxia Vocational Technical College of Industry and Commerce, Yinchuan, China.
Shandong Xiehe University · CNSichuan Cancer Hospital · CNSwansea University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Music therapy is a common method to relieve anxiety and pain in cancer patients after surgery in recent years, but due to the lack of technical and algorithmic support, this therapy is not particularly stable and the therapeutic effect is not good. In this study, a neural network robotic system based on breast cancer patients was designed to analyze the effect of music relaxation training on alleviating adverse reactions after chemotherapy in breast cancer patients. Firstly, this paper introduces the necessity of neural network robot system research under the background of music therapy, and then summarizes the positive effect of music relaxation therapy on alleviating adverse reactions after chemotherapy in breast cancer patients, finally, uses neural network robot system to construct music therapy system. The experimental results show that the new music therapy proposed in this study has a good effect in alleviating the adverse reactions of breast cancer patients after chemotherapy, and the cure rate is increased by 7.84%. The research results of this paper provide reference for the next development of neural network robot system in the medical field.

Indexed as

alleviate adverse reactionsbreast cancerbreast cancer patientsmusic therapyneural network robot system

Identifiers

PMID36741503
PMCPMC9892632
OpenAlexW4319294829

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.