97 eligible studies published between 2015 and May 2025 were analyzed in this systematic review. The review maps the use of artificial intelligence methods, including deep learning and machine learning, for analyzing the behavior of organisms like Drosophila melanogaster and zebrafish larvae. It was authored by Zuzanna Stępnicka and published on figshare in May 2026.
Use Cases
- Benchmark AI methods for behavioral analysis based on the review of 97 studies.
- Identify trends in model organism usage based on the reported frequency of Drosophila melanogaster and Caenorhabditis elegans.
- Evaluate standardization gaps in reporting practices based on the noted inconsistencies in input data and evaluation metrics.
- Guide tool selection for automated observation based on the dominance of convolutional neural networks and pose estimation frameworks since 2021.
- Support preclinical research planning based on the potential to accelerate drug discovery and reduce vertebrate model reliance.
Strengths
- Follows PRISMA 2020 guidelines for systematic review methodology.
- Analyzes 97 studies, showing a steep increase from 2 in 2015.
- Identifies dominant AI methods, such as convolutional neural networks and DeepLabCut.
- Proposes a standardized reporting framework to address reproducibility gaps.
Limitations
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.
- The dataset is 46.6 KB, indicating a limited scope of contained data.
Provenance
- Source
- figshare
- Collection Method
- Systematic literature review following PRISMA 2020 guidelines.
- Time Range
- 2015 to May 2025
- Freshness
- Last updated 2026-05-19 05:41:10; freshness should be verified.