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Tag: Mammography

An artificial intelligence system can reduce false positives and false negatives in prediction of breast cancer and outperforms human readers

AI System Outperforms Radiologists in Breast Cancer Prediction

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Reduction seen in false positives, false negatives in datasets from the United Kingdom, United States
Compared with annual screening

RSNA: Biennial Mammo Returns More Advanced-Stage Cancers

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Annual mammography screening, used by most patients, yields smaller and less advanced cancers
There is no significant difference in breast cancer detection rates with dense breast ultrasound screening following digital mammography versus digital breast tomosynthesis

Cancer Yield Similar for Dense Breast Ultrasound After DM, DBT

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Detection rates for additional cancers similar after digital mammography, digital breast tomosynthesis
Regardless of the percentage of lifetime spent in the United States

Foreign-Born Women in U.S. Less Likely to Have Mammograms

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Findings remain even after adjusting for common sociodemographic factors
Use of a deep learning artificial intelligence system for digital breast tomosynthesis images can improve cancer detection efficacy and reduce image reading time

AI Assists in Reading of Digital Breast Tomosynthesis Images

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Concurrent use of AI system improves cancer detection, reduces reading time and recall rate
Adoption of 3-D mammography expanded rapidly in the United States in just a few years

Use of 3-D Mammography Rapidly Expanded 2015 to 2017

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Adoption varied widely by region; uptake more rapid in areas with greater socioeconomic resources
Use of surveillance breast magnetic resonance imaging is associated with increased biopsy and subsequent cancer detection rates compared with mammography alone among women with a personal history of breast cancer

Surveillance Breast MRI Ups Biopsy, Cancer Detection Rates

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Better results seen compared with mammography alone in women with a personal history of breast cancer
Generally

Mammogram Benefits Seen as More Important Than Harms

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Perception varies by knowledge of latest recommendations, date of last mammogram
New recommendations have been developed for breast cancer screening based on a life-years-gained model; the American Society of Breast Surgeons official statement was published online May 3.

New Recommendations Developed for Breast Cancer Screening

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Guideline based on individual breast cancer risk profile, with specific screening strategies
Mammography-based deep learning breast cancer risk models are more accurate than models that consider traditional risk factors and breast density

Mammo-Based Deep Learning Model Assesses Breast Cancer Risk

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Deep learning models more accurate than models that use traditional risk factors, breast density