ai reduce false positive
AI reduces false positives in screening mammography
Following the assumption that there may be nuanced features associated with some mammogram images that could lead to an unnecessary recall when interpreted by a radiologist, the researchers used a method based on convolutional neural networks (CNNs) to build a computer toolkit that could identify those images. The researchers trained CNN models using 14,860 images of 3,715 patients from the Full-Field Digital Mammography Dataset and the Digital Dataset of Screening Mammography. They investigated six classification scenarios that would help distinguish images of benign, malignant, and recalled-benign mammograms.