Evidence map›Paper›PMID 35845927›Full record

ArticleBioMed research international2022

A Comparison of Decision Tree Algorithms in the Assessment of Biomedical Data.

Fahima Hajjej, Manal Abdullah Alohali, Malek Badr, Md Adnan Rahman

RetractedAbstract readRetracted Publication
In one paragraph

Article in BioMed research international, 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 It has been retracted, and should not be counted.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
–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

3 citing papers in PubMed.

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

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Fahima HajjejDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.ORCID https://orcid.org/0000-0003-1709-5790
Manal Abdullah AlohaliDepartment of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Malek BadrDepartment of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad 10021, Iraq.ORCID https://orcid.org/0000-0002-6183-4207
Md Adnan RahmanGreen Business School, Green University of Bangladesh, Bangladesh.ORCID https://orcid.org/0000-0003-3378-0958

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

By comparing the performance of various tree algorithms, we can determine which one is most useful for analyzing biomedical data. In artificial intelligence, decision trees are a classification model known for their visual aid in making decisions. WEKA software will evaluate biological data from real patients to see how well the decision tree classification algorithm performs. Another goal of this comparison is to assess whether or not decision trees can serve as an effective tool for medical diagnosis in general. In doing so, we will be able to see which algorithms are the most efficient and appropriate to use when delving into this data and arrive at an informed decision.

Indexed as

AlgorithmsArtificial IntelligenceHumansSoftware

Identifiers

PMID35845927
PMCPMC9283053

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.