ArticleJournal of healthcare engineering2022
The Impact of a Knowledge Discovery-Based Psychoanalytic Intervention in the Treatment of Tuberculosis in University Students with Different Doses of Isoniazid.
Article in Journal of healthcare engineering, 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 It has been retracted, and should not be counted.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 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Retracted: The Impact of a Knowledge Discovery-Based Psychoanalytic Intervention in the Treatment of Tuberculosis in University Students with Different Doses of Isoniazid.Journal of healthcare engineering · 2023Article
Corrections and comments
- Retraction · 2023-08-02Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Informed/Patient Consent - None/Withdrawn · Investigation by Journal/Publisher · Investigation by Third Party · Lack of IRB/IACUC Approval and/or Compliance · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/126B4E55E386C1CB308D30CA63A8C3
- Retracted
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tuberculosis (TB) is an infectious disease that poses a serious threat to the health of the population in China, and TB outbreaks in universities have aroused great concern in society. Psychological emotions have a large impact on the academic lives of university students, and nowadays it is not only labour-intensive but also slow to monitor and analyse and deal with the psychology of university students' daily lives in a uniform manner. If psychological problems are not detected and given feedback in a timely manner, they can have a series of negative effects on the individual university student. In this paper, we apply the Bi-LSTM model and the CNN model neural network algorithm to learn the text data, and finally have 95.55% and 90.03% accuracy in the sentiment analysis experiment, respectively, which provides a feasible solution to solve the batch rapid analysis of the psychological changes reflected in the daily text of university students. Risk communication for TB emergencies should emphasize public participation, timely release of information about the epidemic, and good monitoring of public opinion.
Indexed as
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What OpenQuestion holds
Registered trials
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.