AuntMinnie

APRIL 10, 2024

A deep-learning algorithm can rule out the presence of breast cancer on screening mammograms, improving specificity and yielding significant workflow and downstream savings, according to research published April 10 in Radiology. dataset 1: 143,593 mammograms interpreted by 11 breast radiologists from 2008 to 2017 U.S.

Mammogram 85

Mammogram Quality and Compliance Radiologist Radiology 85

AuntMinnie

OCTOBER 25, 2023

In Europe, breast cancer screening involves double reading, where two interpreting radiologists review mammography images. However, radiologist pairing in this setting is done randomly, and screening performance varies among radiologists. per 1,000 exams 54.1 per 1,000 exams Abnormal interpretation rate (England) 68.2-70.5

Radiologist 105

Radiologist Mammogram Medical Imaging 105

AuntMinnie

APRIL 9, 2024

In testing, the score outperformed traditional mammographic density measurements in flagging patients for supplemental breast imaging following a negative screening mammogram. Moreover, this risk categorization might also prompt an additional image review by radiologists, particularly when informed of a high AISmartDensity score.”

Mammogram 85

Mammogram Clinic Imaging Hospital 85

Imaging Technology

SEPTEMBER 24, 2024

The data also suggests that 3D mammograms could reduce the incidence of advanced cancer diagnoses. YSM radiologists at Yale New Haven Health (YNHH) adopted the new DBT technology in 2011. Researchers analyzed 1,407 breast cancer cases detected from August 2008 to July 2021, including 35,544 DM screenings and 237,394 DBT screenings.

Mammogram 52

Mammogram Diagnose Radiology Radiologist 52