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What Artificial Intelligence Can See That We Can’t & How It’s Improving Medicine

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One day in 2017, computational biologist Aristotelis Tsirigos, PhD, strolled into the kitchen near his office in NYU Langone Health’s molecular pathology lab to grab a cup of coffee, and met a new faculty member. When Dr. Tsirigos introduced himself as director of clinical informatics, his new colleague, Narges Razavian, PhD, perked up. She was also a computer scientist, albeit one with a slightly different focus.
While Dr. Tsirigos was applying genomic data to uncover some of the complex cellular processes underlying disease, Dr. Razavian, assistant professor of population health and of radiology, was experimenting with ways to use artificial intelligence, or AI, in the clinic as a diagnostic tool.
But like most researchers at the intersection of AI and medicine, her big challenge was finding enough patient data to properly train her software to recognize the telltale markers of pathology. As it happened, pulling together large databases of patient data was one of Dr. Tsirigos’s specialties—and so a fruitful partnership was born.
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