Evidence map›Paper›PMID 31885684›Full record

ArticleComputational and mathematical methods in medicine2019

A Feature-Driven Decision Support System for Heart Failure Prediction Based on

Liaqat Ali, Shafqat Ullah Khan, Noorbakhsh Amiri Golilarz, Imrana Yakubu, Iqbal Qasim, Adeeb Noor, Redhwan Nour

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  7. Sensors (Basel, Switzerland) · 2022
    Article
  8. Article
  9. Article
  10. Review
  11. A hybrid cost-sensitive ensemble for heart disease prediction.BMC medical informatics and decision making · 2021
    Article
  12. 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

7 authors.

Liaqat AliSchool of Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.ORCID https://orcid.org/0000-0002-3095-7271
Shafqat Ullah KhanDepartment of Electronics, University of Buner, Buner 17290, Pakistan.ORCID https://orcid.org/0000-0003-1969-1289
Noorbakhsh Amiri GolilarzSchool of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
Imrana YakubuSchool of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.ORCID https://orcid.org/0000-0002-9901-4909
Iqbal QasimDepartment of Computer Science, University of Science and Technology, Bannu 28100, Pakistan.
Adeeb NoorDepartment of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 80221, Saudi Arabia.ORCID https://orcid.org/0000-0002-8251-1853
Redhwan NourDepartment of Computer Science, Taibah University, Medina 42353, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heart failure (HF) is considered a deadliest disease worldwide. Therefore, different intelligent medical decision support systems have been widely proposed for detection of HF in literature. However, low rate of accuracies achieved on the HF data is a major problem in these decision support systems. To improve the prediction accuracy, we have developed a feature-driven decision support system consisting of two main stages. In the first stage,

Indexed as

Decision Support TechniquesBayes TheoremComputational BiologyDatabases, FactualDecision Support Systems, ClinicalDiagnosis, Computer-AssistedExpert SystemsHeart FailureHumansMachine LearningModels, StatisticalNormal DistributionSupport Vector Machine

Identifiers

PMID31885684
PMCPMC6925936

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Registered trials

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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.