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    Pigeons Can Identify Breast Cancer In Tissue Samples 'As Well As Humans'

    ByAllison EckNOVA NextNOVA Next

    Pigeons have been trained by the U.S. Coast Guard to spot shipwrecked sailors’ orange life jackets. They can recognize the 26 letters of the English alphabet. And they’ve been savvy messengers in times of both war and peace.

    Now, scientists have taught them how to identify breast cancer.

    As part of the experiment, each bird learned what malignant and benign cancer slides look like at a range of magnifications and compression levels. After two weeks of training, the pigeon participants in the study— published in the journal Plos One—had achieved an 85% accuracy rate in their ability to distinguish cancerous breast tissue samples from healthy ones. And when the scientists tried “crowdsourcing” four individual birds’ verdicts, they were able to arrive at an accurate diagnosis 99% of the time.

    Pigeons are incredibly smart birds—and we can use that to our advantage.

    The team, led by Richard Levenson of the University of California at Davis, also tested pigeons’ mammogram-reading capabilities. In this case, the birds could identify the small deposits in mammogram images that are indicative of a pre-cancerous growth.

    Here’s Andrea Szöllössi, reporting for the BBC:

    However, when the team put the pigeons to work classifying suspicious masses – an important but difficult job for clinicians themselves – they were unable to recognise the lumps with malignant potential.

    “As this task reflects the difficulty even humans have, it indicates how pigeons may be faithful mimics of the strengths and weaknesses of humans in viewing medical images,” Prof Levenson said.

    It’s unlikely that hospitals and labs will request deliveries of pigeons en masse as part of their diagnostic toolkit any time soon. But since pigeons’ perceptual tendencies seem to resemble our own (at least in this scenario), this research could help engineers create better image-recognition and diagnostic tools.

    Photo credit: Filip Wojciechowski / Flickr (CC BY-NC 2.0)

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