The idea of using dogs’ noses to detect the scent of human cancer has been around for decades, and researchers have even tried building machines to do the job, but none have been able to match the sensitivity of man’s best friend. Rather than try to compete with evolution, scientists decided to bring in the experts. In a proof-of-concept study, researchers used dogs to train a machine learning algorithm to detect prostate cancer, the second most common cancer in men. Because the study included a small number of samples—from 50 men, of whom only 12 had a positive biopsy—the dogs didn’t achieve the sensitivity and specificity that other canines have been able to, but it’s a promising first step, according to Marc Aubreville, a professor of image understanding and medical application of artificial intelligence at Germany’s Technische Hochschule Ingolstadt, who wasn’t involved in the work. “It’s really interdisciplinary what they’re ...
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Amanda first began dabbling in scicom as a master’s student studying marine science at Moss Landing Marine Labs, where she edited the student blog and interned at a local NPR station. She enjoyed that process of demystifying science so much that after receiving her degree in 2019, she went straight into a second master’s program in science communication at the University of California, Santa Cruz. Formerly an intern at The Scientist, Amanda joined the team as a staff reporter and editor in 2021 and oversaw the publication’s internship program, assigned and edited the Foundations, Scientist to Watch, and Short Lit columns, and contributed original reporting across the publication. Amanda’s stories often focus on issues of equity and representation in academia, and she brings this same commitment to DEI to the Science Writers Association of the Rocky Mountains and to the board of the National Association of Science Writers, which she has served on since 2022. She is currently based in the outdoor playground that is Moab, Utah. Read more of her work at www.amandaheidt.com.
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