ArticleiScience2024
AI-powered home cage system for real-time tracking and analysis of rodent behavior.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Activity as a readout parameter for neurobehavioral research and severity assessment in laboratory rodents: a systematic comparison and meta-analysis of measurement techniques.Scientific reports · 2026Pooled it
- Artificial Intelligence in Veterinary Neurology: Comparative Insights From Human Medicine and Cross-Species Technology Transfer.Veterinary medicine and science · 2026Review
- The emerging roles of long non-coding RNAs in the nervous system.Nature reviews. Neuroscience · 2025Review
- Rodent Social Behavior Recognition Using a Global Context-Aware Vision Transformer Network.AI (Basel, Switzerland) · 2025Article
- Assessing cognitive flexibility in mice using a custom-built touchscreen chamber.Frontiers in behavioral neuroscience · 2025Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Researchers in animal behavior and neuroscience devote considerable time to observing rodents behavior and physiological responses, with AI monitoring systems reducing personnel workload. This study presents the RodentWatch (RW) system, which leverages deep learning to automatically identify experimental animal behaviors in home cage environments. A single multifunctional camera and edge device are installed inside the animal's home cage, allowing continuous real-time monitoring of the animal's behavior, position, and body temperature for extended periods. We investigated identifying the drinking and resting behaviors of rats, with recognition accuracy enhanced through contextual object labeling and modified non-maximum suppression (NMS) schemes. Two tests-a light cycle change test and a sucrose preference test-were conducted to evaluate the usability of this system in rat behavioral experiments. This system enables notable advancements in image-based behavior recognition for living rodents.
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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.