16 DAILY MICCAI Tuesday Poster Presentation detection allowed the founders to forge close relationships with radiologists, staff, and patients. It cemented their desire to make products that have a meaningful impact on clinical outcomes. “We want to come up with products that help detect breast cancer earlier,” Nhi says. “This doesn’t just come from something like our paper, which looks at the mammogram and detects the cancer, but we also try to improve the experience. It’s not just about accuracy. You can say your model has very high sensitivity, but what if it creates a lot of false positives? As a company, we’re very careful about the different aspects and consequences related to mammography. I feel lucky to be surrounded by people like Thomas and our CTO, Jason Su. They care about the problem and the clinical outcome as opposed to just making the biggest, most data-efficient model.” In closing, the message from Nhi and Dan’s research is clear. When addressing a meaningful problem like reducing false positives in breast cancer screening, it’s essential to identify and tackle the underlying challenges. “Essentially, the key idea is to find aspects of medical imaging that may not exist in the usual natural image computer vision sphere and try to use them to tackle these very special aspects of mammography,” Nhi adds. “It’s not like we can just bring something from detecting dogs and cats over and apply it to patients!” To learn more about Nhi and Dan’s work, visit Poster 4 this afternoon at 13:00-14:30 in the Poster Hall.
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