Medical Research Council - London Institute of Medical Sciences

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Imperfect Education

More experts are better than one for training bioimage interpretation algorithms

03 January 2021

Imperfect Education

Making observations of life is the most fundamental discovery process of biology. Today’s imaging technology shows scientists more detail than ever before, with vast and complex image sets produced in labs around the world every day. Analysing these data takes specialist skills and lots of time, and is subject to the individual analyst’s subjective perspective. Automating the process would speed it up and remove inconsistencies. Machine algorithms must be trained by examples, however, so it’s possible that they might replicate the subjectivity they aim to eradicate if trained by one expert’s examples. To investigate, researchers compared algorithms trained on a single expert’s work to those trained on many experts’ analyses (pictured, with different experts’ marks on a mouse brain image in different colours). Training the algorithm with many people’s input reduced subjectivity and improved outcomes, showing that many teachers are better than one.

Written by Anthony Lewis

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