ReviewMedical & biological engineering & computing2023
Unlocking the Potential of Zebrafish Research with Artificial Intelligence: Advancements in Tracking, Processing, and Visualization.
Review in Medical & biological engineering & computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 25 citations in OpenAlex.
- Zebrafish as a versatile model in biomedical research, from disease modeling to regenerative medicine: a review.Fish physiology and biochemistry · 2026Review
- Emerging trends and clinical challenges in AI-enhanced emotion diagnosis using physiological data.Medical & biological engineering & computing · 2026Review
- Zebrafish as a translational model for peptide-mediated synaptic dysfunction related to obesity.Frontiers in synaptic neuroscience · 2026Review
- Zebrafish: A Versatile and Powerful Model for Biomedical Research.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025Review
- Zebrafish as a model for assessing biocide toxicity: A comprehensive review.Toxicology reports · 2025Review
- Experimental modeling of Alzheimer's disease: Translational lessons from cross-taxon analyses.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Review
- Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.Communications biology · 2025Article
- Small Fish, Big Answers: Zebrafish and the Molecular Drivers of Metastasis.International journal of molecular sciences · 2025Review
- Behavioral Studies of Zebrafish Reveal a New Perspective on the Reproductive Toxicity of Micro- and Nanoplastics.Toxics · 2024Review
- Exploring the use of deep learning models for accurate tracking of 3D zebrafish trajectories.Frontiers in bioengineering and biotechnology · 2024Article
- Recent Advances in Bioimage Analysis Methods for Detecting Skeletal Deformities in Biomedical and Aquaculture Fish Species.Biomolecules · 2023Review
- Sixty years in service to international biomedical engineering community.Medical & biological engineering & computing · 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
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Zebrafish have become a widely accepted model organism for biomedical research due to their strong cortisol stress response, behavioral strain differences, and sensitivity to both drug treatments and predators. However, experimental zebrafish studies generate substantial data that must be analyzed through objective, accurate, and repeatable analysis methods. Recently, advancements in artificial intelligence (AI) have enabled automated tracking, image recognition, and data analysis, leading to more efficient and insightful investigations. In this review, we examine key AI applications in zebrafish research, including behavior analysis, genomics, and neuroscience. With the development of deep learning technology, AI algorithms have been used to precisely analyze and identify images of zebrafish, enabling automated testing and analysis. By applying AI algorithms in genomics research, researchers have elucidated the relationship between genes and biology, providing a better basis for the development of disease treatments and gene therapies. Additionally, the development of more effective neuroscience tools could help researchers better understand the complex neural networks in the zebrafish brain. In the future, further advancements in AI technology are expected to enable more extensive and in-depth medical research applications in zebrafish, improving our understanding of this important animal model. This review highlights the potential of AI technology in achieving the full potential of zebrafish research by enabling researchers to efficiently track, process, and visualize the outcomes of their experiments.
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.