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Machine learning: improving the process of annotating animal data
Machine learning, and its deep learning offshoot, is a fast-paced field that’s starting to make its mark in the animal lab, particularly in areas marked by repetitive tasks. Behavioral phenotyping—identifying what an animal is doing—is an important aspect of animal research, but it has long relied on manpower. If a human can do it, can a computer do it too?
Getting there means finding the right algorithm and adapting it to a particular research question, and then training the system to make the right predictions. For the less computer-savvy, many developers are also working on graphical user interfaces to get their tools into more hands. It can be a big task, but algorithms are becoming more sophisticated, and, if properly trained, may help eliminate or reduce the need for a human to work through increasing hours of recordings to annotate and label their animal data.
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