Systematic Review of AI Use in Invertebrate Behavioral Analysis, 2015-2025

Zuzanna Stępnicka's systematic review maps the use of artificial intelligence for behavioral analysis of invertebrate and larval model organisms. The review, published on figshare in May 2026, analyzes 97 eligible studies published between 2015 and May 2025. It examines model organisms, AI methods, input data characteristics, and evaluation metrics.

Use Cases

• Benchmarking AI model performance for behavioral classification based on the review of 97 studies.
• Designing standardized data preprocessing pipelines based on reported inconsistencies in video/image recording practices.
• Selecting appropriate model organisms for new experiments based on the frequency of study for species like D. melanogaster and C. elegans.
• Informing the development of reproducible evaluation frameworks based on the identified gaps in reporting metrics.

Strengths

• Follows PRISMA 2020 guidelines for systematic review methodology.
• Analyzes a defined corpus of 97 studies published over a 10-year period (2015-2025).
• Identifies specific trends, such as the dominance of deep learning models like CNNs since 2021.
• Proposes a concrete standardized reporting framework to address identified gaps.

Limitations

• The dataset is a 27.0 KB DOCX document, indicating a limited scope of raw data.
• Row count and column-level documentation are absent; the content is a review article.
• The data is a secondary analysis, so original experimental data is not included.

Provenance

Source

Zuzanna Stępnicka via figshare.

Collection Method

Systematic literature review following PRISMA 2020 guidelines.

Time Range

Studies published between 2015 and May 2025.

Freshness

Last updated 2026-05-19 05:41:09.

Geography

Studies primarily originated from the USA, China, and Germany.