ArticleAI in neuroscience2025
DeepLabCut to Automate Behavioral Analysis of Parkinsonism.
Article in AI in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Comparative Evaluation of DeepLabCut Convolutional Neural Network Architectures for High-Precision Markerless Tracking in the Mouse Staircase Test.Bioengineering (Basel, Switzerland) · 2026Article
- Rigorous Validation of Paw Preference Using Three Complementary Behavioral Assays in Sprague Dawley Rats.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Background: Behavioral assessment of parkinsonism often relies on human rater evaluation. However, human biases and variability necessitate larger sample sizes to maintain validity, leading to extensive video analysis and limiting researchers' time. Recent artificial intelligence (AI) and machine learning (ML) advancements enable efficient data analysis, offering unbiased decision-making and consistency across scenarios, bridging inter-rater differences. While not fully automating jobs, AI/ML boosts productivity when properly trained with diverse data. This study aims to show that AI/ML can assist in the analysis of rat parkinsonian behavioral studies to reduce labor dependence while still maintaining accuracy. Methods: DeepLabCut (DLC), an animal pose estimation software, was used to analyze motor behavior in video recordings of parkinsonian Sprague Dawley rats while they performed the stepping test ( Results: There was good absolute agreement between the two scoring methods, using the two-way random effect model, kappa = 0.9,
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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.