Table 8_Systematic review of artificial intelligence use in behavioral analysis of inverte

Zuzanna Stępnicka's systematic review comprehensively maps the use of artificial intelligence in behavioral analysis of invertebrate and larval organisms. It analyzes 97 eligible studies published between 2015 and May 2025, covering model organisms, AI methods, input data characteristics, preprocessing pipelines, model architectures, and evaluation metrics. The review proposes a standardized reporting framework to enhance transparency and reproducibility.

Use Cases

• Benchmarking AI methods for behavioral analysis based on the review of 97 studies.
• Identifying trends in model organism usage and AI techniques from 2015 to 2025.
• Developing standardized reporting frameworks for behavioral AI research based on identified gaps.
• Selecting appropriate preprocessing pipelines and model architectures for new behavioral studies.

Strengths

• Follows PRISMA 2020 guidelines for systematic review methodology.
• Analyzes 97 studies, showing a steep increase from 2 in 2015 to 97 by mid-2025.
• Identifies dominant AI techniques like convolutional neural networks and pose estimation frameworks since 2021.

Limitations

• The dataset is a 274.0 KB DOCX file, which is a text document rather than a structured data table.
• Row count and column-level documentation are absent; data is presented as a review narrative.
• Freshness should be verified; last updated date is 2026-05-19.

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 05:41:08.

Geography

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