Evidence map›Paper›PMID 41244694›Full record

ArticleFrontiers in microbiology2025

Rapid and accurate recognition of erythrocytic stage parasites of

Wei He, Huiyin Zhu, Junjie Geng, Daiqian Zhu, Kai Wu, Li Xie, Jian Li, Hailin Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Wei He *Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, China.
Huiyin Zhu *Department of Human Parasitology, School of Basic Medicine Science, Hubei University of Medicine, Shiyan, China.
Junjie GengSchool of Internet of Things Engineering, Jiangnan University, Wuxi, China.
Daiqian ZhuDepartment of Human Parasitology, School of Basic Medicine Science, Hubei University of Medicine, Shiyan, China.
Kai WuWuhan City Center for Disease Prevention and Control, Wuhan, China.
Li XieSchool of Internet of Things Engineering, Jiangnan University, Wuxi, China.
Jian LiDepartment of Human Parasitology, School of Basic Medicine Science, Hubei University of Medicine, Shiyan, China.
Hailin YangKey Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Malaria remains a fatal global infectious disease, with the erythrocytic stage of Methods: The peripheral blood samples of malaria patients were collected. Thin blood film smear were prepared, stained and examined by microscopic. After manual confirmation and validation with qPCR, the images of infected red blood cells (iRBCs) of Results: A total of 262 images were tested. The YOLOv3 model detected 358 Conclusion: The developed AI-assisted diagnostic tool exhibits robust efficiency and accuracy in

Indexed as

artificial intelligencedeep learningmalariaPlasmodium falciparumyou only look once

Identifiers

PMID41244694
PMCPMC12611930

What OpenQuestion holds

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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.