In scientific research, objectivity and unbiased data analysis is crucial for the validity and reproducibility of outcomes. This is particularly important for studies involving video or image categorization. A common approach of decreasing the bias is delegating data analysis to researchers unfamiliar with the experimental settings. However, this requires additional personnel and is prone to cognitive biases. Here we describe the Video & Image Cutter & Randomizer (VICR) software (https://github.com/kkihnphd/VICR), designed for unbiased analysis by segmenting and then randomizing the segmented videos or still images. VICR allows a single researcher to conduct and analyze studies in a blinded manner, eliminating the bias in analysis and streamlining the research process. We describe the features of the VICR software and demonstrate its capabilities using zebrafish behavior studies. To our knowledge, VICR is the only software for the randomization of video and image segments capable of eliminating bias in data analysis in a variety of research fields.
VICR: A novel software for unbiased video and image analysis in scientific research.
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作者:Kihn Kyle, Thomas Clementine A D, Brelidze Tinatin I
| 期刊: | PLoS One | 影响因子: | 2.600 |
| 时间: | 2024 | 起止号: | 2024 Oct 24; 19(10):e0312619 |
| doi: | 10.1371/journal.pone.0312619 | ||
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