Evidence map›Paper›PMID 35669979›Full record

ArticleJournal of healthcare engineering2022

Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh.

Md Ismail Hossain, Md Jakaria Habib, Ahmed Abdus Saleh Saleheen, Md Kamruzzaman, Azizur Rahman, Sutopa Roy, Md Amit Hasan, Iqramul Haq, Md Injamul Haq Methun, Md Iqbal Hossain Nayan and 1 more

Open access · hybridAbstract read
In one paragraph

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. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

11 authors at 4 institutions in 1 country.

Md Ismail HossainDepartment of Statistics, Jagannath University, Dhaka 1100, Bangladesh.ORCID 0000-0002-5645-2095
Md Jakaria HabibDepartment of Statistics, Jagannath University, Dhaka 1100, Bangladesh.
Ahmed Abdus Saleh SaleheenDepartment of Statistics, Jagannath University, Dhaka 1100, Bangladesh.
Md KamruzzamanDepartment of Statistics, Jagannath University, Dhaka 1100, Bangladesh.
Azizur RahmanDepartment of Statistics, Jahangirnagar University, Savar, Dhaka, Bangladesh.
Sutopa RoyDepartment of Statistics, Jagannath University, Dhaka 1100, Bangladesh.
Md Amit HasanDepartment of Statistics, Jagannath University, Dhaka 1100, Bangladesh.
Iqramul HaqDepartment of Agricultural Statistics, Sher-e-Bangla Agricultural University, Dhaka 1207, Bangladesh.ORCID 0000-0002-9183-120X
Md Injamul Haq MethunStatistics Discipline, Tejgaon College, Dhaka 1215, Bangladesh.
Md Iqbal Hossain NayanQuality Services and Compliance, Square Pharmaceutical Limited, Dhaka, Bangladesh.
Md Rukonozzaman RukonDepartment of Statistics, Jagannath University, Dhaka 1100, Bangladesh.
Jagannath University · BDJahangirnagar University · BDSher-e-Bangla Agricultural University · BDSquare Hospitals · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intended pregnancy is one of the significant indicators of women's well-being. Globally, 74 million women become pregnant every year without planning. Unintended pregnancies account for 28% of all pregnancies among married women in Bangladesh. This study aimed to investigate the performance of six different machine learning (ML) algorithms applied to predict unintended pregnancies among married women in Bangladesh. From BDHS 2017-18, only 1129 pregnant women aged 15-49 were eligible for this study. An independent

Indexed as

Machine LearningPregnancy, UnplannedAlgorithmsBangladeshBayes TheoremFemaleHumansMalePregnancySupport Vector Machine

Identifiers

PMID35669979
PMCPMC9167128
OpenAlexW4281873287

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.