ArticleScientific data2025
Inner Ear Multiple Primary Cell Type Detection System.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- Advances and prospects of 3D air-liquid interface cultured middle ear epithelial cells and inner ear organoids in otologic diseases.Frontiers in bioengineering and biotechnology · 2026Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In vitro inner ear organoids gene therapy has advanced medical development, yet extracting inner ear primary cells (IEP) remains complex and needs to scarify mice. IEP cells contain multiple cell types, including progenitor cells, which can differentiate into hair-progenitor or neuro-progenitor cells. Accurate cell detection is essential to understand cell interactions and optimize culture conditions, ultimately reducing the sacrifice of mice. Current commercial software counts only one cell type at a time, often making errors in aggregated regions and taking at least five minutes per count. This paper proposes the Inner Ear Multiple Primary Cell Type Detection System (IEP-CDS), which addresses data limitations through IEP augmentation, overcomes detection errors in aggregated regions using preprocessing methods for training YOLO models, and achieves an F1-score greater than 20% compared to commercial software, completing counts in under one second. Furthermore, IEP-CDS provides rare IEP image data with expert labels. Overall, IEP-CDS effectively improves the efficiency of IEP detection in developing cell therapy for inner ear organoids.
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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.