Evidence map›Paper›PMID 38313031›Full record

ArticlePeerJ2024

Automatic detection of

Tongjit Thanchomnang, Natthanai Chaibutr, Wanchai Maleewong, Penchom Janwan

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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

4 authors at 3 institutions in 1 country.

Tongjit ThanchomnangFaculty of Medicine, Mahasarakham University, Maha Sarakham, Thailand.
Natthanai ChaibutrMedical Innovation and Technology Program, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand.
Wanchai MaleewongDepartment of Parasitology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.ORCID 0000-0002-6726-3759
Penchom JanwanMedical Innovation and Technology Program, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand.
Walailak University · THKhon Kaen University · THMahasarakham University · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Human opisthorchiasis is a dangerous infectious chronic disease distributed in many Asian areas in the water-basins of large rivers, Siberia, and Europe. The gold standard for human opisthorchiasis laboratory diagnosis is the routine examination of Methods: Herein, we propose a convolutional neural network (CNN) for classifying and automatically detecting Results: The proposed model, initially trained on non-augmented data of artifacts (class 0) and Conclusion: This study demonstrated the successful application of CNN in classifying and automating the detection of

Indexed as

OpisthorchiasisOpisthorchisAnimalsFecesHumansNeural Networks, ComputerResearch DesignConvolutional neural networksDeep learningHuman opisthorchiasisMicroscopic detection

Identifiers

PMID38313031
PMCPMC10836206
OpenAlexW4391354208

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.