Evidence map›Paper›PMID 35463263›Full record

ArticleComputational intelligence and neuroscience2022

Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

Kangqi An

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 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 It has been retracted, and should not be counted.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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 29% 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, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Kangqi AnSchool of Psychological and Cognitive Sciences, Peking University, Beijing 100871, China.ORCID https://orcid.org/0000-0001-7457-0151
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It was to explore the application value of health cloud service platform based on data mining algorithm and wireless network in the analysis of psychosocial factors and psychological characteristics of personality of patients with chronic diseases. Based on the demand analysis of cloud service platform for chronic diseases, a health cloud service platform including three modules was established: support layer, application layer, and interaction layer; and K-means algorithm and Apriori algorithm were used to mine and process data. The changes of pulse wave and EEG signal of epileptic seizures before and after processing by wireless network health cloud service platform were analyzed. 42 patients with idiopathic generalized epilepsy were selected as the research subjects, and 40 volunteers with normal physical examination during the same period were selected as the control group. The differences in the basic clinical characteristics data, Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), Symptom Checklist 90 (SCL-90), and Eysenck Personality Questionnaire-Revision Short Scale for Chinese (EPQ-RSC) were compared between the two groups. It was found that the initial EEG signals of epileptic patients had noise pollution before and after the seizure, and the noise in the EEG signals was filtered out after digital technology processing in the cloud service platform. The maximum number of epileptic patients aged 18∼30 years was 17 (40.48%), and the mean scores of HAMD and HAMA scales in the epileptic group were significantly higher than those in the control group (

Indexed as

Artificial IntelligenceCloud ComputingChronic DiseaseData MiningHumansPersonalitySurveys and QuestionnairesTechnology

Identifiers

PMID35463263
PMCPMC9020898
OpenAlexW4224111212

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.