ArticleFrontiers in microbiology2022
A study on the diagnosis of the
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
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Who cites it
9 citing papers in PubMed, 20 citations in OpenAlex.
- Phenotypic and Genotypic Characterization of Antimicrobial Resistance inInternational journal of microbiology · 2026Article
- Rapid and Efficient Screening ofDiagnostics (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Bacterial Infections Control: A Scoping Review.Antibiotics (Basel, Switzerland) · 2025Review
- Co-culture of Helicobacter pylori with oral microorganisms in human saliva.Clinical oral investigations · 2025Article
- Nanomaterials: A Prospective Strategy for Biofilm-FormingInternational journal of nanomedicine · 2025Review
- Antimicrobial susceptibility of clinicalMicrobiology spectrum · 2024Article
- Pathohistological Changes in the Gastric Mucosa in Correlation with the Immunohistochemically Detected Spiral and Coccoid Forms ofMicroorganisms · 2024Article
- Diagnosis of cervical lymphoma using a YOLO-v7-based model with transfer learning.Scientific reports · 2024Article
- Deep learning assisted diagnosis system: improving the diagnostic accuracy of distal radius fractures.Frontiers in medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Materials and methods: We manually labeled 4,547 images from anonymized paraffin-embedded samples in the China Center for Results: For the HPCF detection task, the YOLO v5 model was superior to the Faster R-CNN model (0.688 vs. 0.568, mean average precision, mAP); the optimized YOLO v5 model had a better performance (0.803 mAP). The MAE of the optimized YOLO v5 model (3.25 MAE) was superior to that of junior pathologists (4.14 MAE, Conclusion: HPCF identification using AI has the advantage of high accuracy and efficiency with the potential to assist or replace pathologists in clinical practice for HPCF identification.
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Identifiers
What OpenQuestion holds
Registered trials
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.