Evidence map›Paper›PMID 35154360›Full record

ArticleComputational and mathematical methods in medicine2022

Artificial Intelligence Technology-Based Medical Information Processing and Emergency First Aid Nursing Management.

Qing Liu, Liping Yang, Qingrong Peng

RetractedAbstract 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 It has been retracted, and should not be counted.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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Qing LiuDepartment of Emergency, The First People's Hospital of Lianyungang, Lianyungang City, 222002, China.ORCID https://orcid.org/0000-0003-0745-1827
Liping YangDepartment of Emergency, The First People's Hospital of Lianyungang, Lianyungang City, 222002, China.ORCID https://orcid.org/0000-0002-4485-9699
Qingrong PengDepartment of Emergency, The First People's Hospital of Lianyungang, Lianyungang City, 222002, China.ORCID https://orcid.org/0000-0002-5188-5377

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was aimed at exploring the new management mode of medical information processing and emergency first aid nursing management under the new artificial intelligence technology. This study will use the artificial intelligence algorithm to optimize medical information processing and emergency first aid nursing management process, in order to improve the efficiency of emergency department and first aid efficiency. The successful rescue rates of hemorrhagic shock, coma, dyspnea, and more than three organs injury were 96.7%, 92.5%, 93.7%, and 87.2%, respectively, after the emergency first aid nursing mode was used in the hospital emergency center. The success rates of first aid within three years were compared, which were 91.8%, 93.4%, and 94.2%, respectively, showing an increasing trend year by year. 255 emergency patients in five batches in June and five batches in July were selected as the research objects by convenience sampling method. Among them, 116 cases in June were taken as the experimental group, and 139 cases in July were taken as the control group, which was used to verify the efficiency of the design model in this study. The results showed that the triage time of the two groups was 8.16 ± 2.07 min and 19.21 ± 6.36 min, respectively, and the difference was statistically significant (

Indexed as

Artificial IntelligenceAdolescentAdultAgedAlgorithmsChildChild, PreschoolChinaComputational BiologyEmergency NursingEmergency Service, HospitalFemaleFirst AidHumansMaleMedical Informatics

Identifiers

PMID35154360
PMCPMC8837421

What OpenQuestion holds

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LicenceCC BY
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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.