BREAST CANCER SCREENING

This study compares using artificial intelligence (AI) to assist a single radiologist in reading mammograms versus the standard practice of having two radiologists read them without AI. About 8,000 women aged 45-69 undergoing routine breast cancer screening will take part. The go…

This large trial tests whether an FDA-approved artificial intelligence tool helps radiologists detect breast cancer more accurately on screening mammograms. About 400,000 adult women across six U.S. health systems will have their mammograms read either with or without AI assistan…

This study compares a new breast imaging system (MAMMOMAT B.brilliant) with a standard one to see if it shows tiny calcium deposits (calcifications) more clearly. About 100 women with suspicious calcifications will get both scans. The goal is to improve detection without changing…

This study tests whether using artificial intelligence (AI) to assist breast ultrasound and mammography can find breast cancer earlier and more accurately in a large group of women. About 16,000 women aged 35 to 69 will be split into two groups: one gets AI-assisted imaging, the …

This study compares two ways of screening for breast cancer: the usual annual mammogram versus a personalized schedule based on each woman's personal risk. Researchers will use family history, genetics, and breast density to tailor screening frequency. The goal is to see if perso…

This study aims to see if offering combined breast and colon cancer screening navigation, along with genetic risk assessment, helps more Black and Hispanic women aged 45-74 get screened. Participants will be assigned to either bundled multi-cancer navigation or single-cancer navi…

This study looks at how breast density affects mammogram results in women aged 45 to 75. Dense breast tissue can make it harder to see cancer on a mammogram, leading to missed cancers or unnecessary extra tests. Researchers will review past screening data and test a software tool…