ArticleScientific reports2021
Zebrafish behavior feature recognition using three-dimensional tracking and machine learning.
Article in Scientific reports, 2021. 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, 33 citations in OpenAlex.
- BullFish: Software for an automated stepwise analysis of positional and postural kinematics of zebrafish locomotion.iScience · 2026Article
- Zebrafish as a translational model for peptide-mediated synaptic dysfunction related to obesity.Frontiers in synaptic neuroscience · 2026Review
- Article
- Article
- Zebrafish as a model for assessing biocide toxicity: A comprehensive review.Toxicology reports · 2025Review
- Advancements in the Developmental Zebrafish Model for Predictive Human Toxicology.Current opinion in toxicology · 2025Article
- High throughput machine learning pipeline to characterize larval zebrafish motor behavior.PloS one · 2025Article
- Deep phenotypic profiling of neuroactive drugs in larval zebrafish.Nature communications · 2024Article
- 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
- Unlocking the Potential of Zebrafish Research with Artificial Intelligence: Advancements in Tracking, Processing, and Visualization.Medical & biological engineering & computing · 2023Review
- Article
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
In this work, we aim to construct a new behavior analysis method by using machine learning. We used two cameras to capture three-dimensional (3D) tracking data of zebrafish, which were analyzed using fuzzy adaptive resonance theory (FuzzyART), a type of machine learning algorithm, to identify specific behavioral features. The method was tested based on an experiment in which electric shocks were delivered to zebrafish and zebrafish swimming was tracked in 3D simultaneously to find electric shock-associated behaviors. By processing the obtained data with FuzzyART, we discovered that distinguishing behaviors were statistically linked to the electric shock based on the machine learning algorithm. Moreover, our system could accept user-supplied data for detection and quantitative analysis of the behavior features, such as the behavior features defined by the 3D tracking analysis above. This system could be applied to discover new distinct behavior features in mutant zebrafish and used for drug administration screening and cognitive ability tests of zebrafish in the future.
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.