ArticleFrontiers in pharmacology2022
A novel deep learning segmentation model for organoid-based drug screening.
Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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.
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.
Who cites it
17 citing papers in PubMed, 14 citations in OpenAlex.
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- From pixels to patterns: the AI revolution in stem cell-derived models.Nature methods · 2026Review
- Review
- Bladder cancer organoids in precision medicine: bridging basic science, clinical therapeutics and drug development.Cancer cell international · 2026Review
- Tumor organoid platform design for drug response modeling: culture architecture, microenvironmental complexity, and AI-assisted readouts.Archives of pharmacal research · 2026Review
- Harnessing Cancer Stem Cells and 3D Organoids in Unravelling Spatial and Cellular Heterogeneity in Cancer.International journal of molecular sciences · 2026Review
- Organoids in drug development: from predictive models to regulatory integration.Drug discovery today · 2026Review
- Organoids and AI-integrated models in ovarian cancer research: the future of personalized therapy.Frontiers in oncology · 2026Review
- Revolutionizing transdermal drug delivery evaluation: the evolution from traditional models to skin organoids and the integration of artificial intelligence.Frontiers in pharmacology · 2026Review
- Urine-derived induced pluripotent stem cells for non-invasive diagnosis of bladder cancer.Journal of Cancer · 2026Review
- Lightweight Deep Learning Model for Classification of Normal and Abnormal Vasculature in Organoid Images.Sensors (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Organoid-Based Disease Modeling: A New Frontier in Precision Medicine.Biomimetics (Basel, Switzerland) · 2025Review
- Computer models and artificial intelligence increase the fidelity and efficiency of the in vitro models for hearing loss.Biomedical engineering online · 2025Review
- 3D-Organoid-SwinNet: High-Content Profiling of 3D Organoids.IEEE journal of biomedical and health informatics · 2025Article
- Harnessing the power of artificial intelligence for human living organoid research.Bioactive materials · 2024Review
- [A review on depth perception techniques in organoid images].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2024Review
- A Convexity-Preserving Level-Set Method for the Segmentation of Tumor Organoids.Bioengineering (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Organoids are self-organized three-dimensional
Indexed as
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.