Evidence map›Paper›PMID 38258027›Full record

ArticleMicroorganisms2024

U

Libo Cao, Liping Zeng, Yaoxuan Wang, Jiayi Cao, Ziyu Han, Yang Chen, Yuxi Wang, Guowei Zhong, Shanlei Qiao

Abstract read
In one paragraph

Article in Microorganisms, 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
–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

4 citing papers in PubMed.

  1. Emerging point-of-care technologies for bacterial pathogen detection.Journal of Zhejiang University. Science. B · 2026
    Review
  2. Review
  3. Article
  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

9 authors.

Libo CaoCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.
Liping ZengDepartment of Pathogen Biology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing 211166, China.
Yaoxuan WangCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.
Jiayi CaoCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.ORCID 0009-0002-8315-4840
Ziyu HanCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.
Yang ChenCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.
Yuxi WangCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.
Guowei ZhongCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.
Shanlei QiaoCenter for Global Health, Nanjing Medical University, Nanjing 211166, China.

Funding

National Natural Science Foundation of China 82202531
6 · The paper itself

Abstract

In this paper, an automatic colony counting system based on an improved image preprocessing algorithm and convolutional neural network (CNN)-assisted automatic counting method was developed. Firstly, we assembled an LED backlighting illumination platform as an image capturing system to obtain photographs of laboratory cultures. Consequently, a dataset was introduced consisting of 390 photos of agar plate cultures, which included 8 microorganisms. Secondly, we implemented a new algorithm for image preprocessing based on light intensity correction, which facilitated clearer differentiation between colony and media areas. Thirdly, a U

Indexed as

bacterial colony countingconvolutional neural networksimage segmentationimage spatial normalizationlight intensity correctionResNet50U2-Net

Identifiers

PMID38258027
PMCPMC10820204

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.