Results 31 to 40 of about 65,767 (202)
What's New? The World Health Organization's Global Breast Cancer Initiative set the benchmark to diagnose breast cancer within 2 months of the first contact with a health care provider. This study analyzed the diagnostic journey of women with breast symptoms at five Ethiopian hospitals. Of the 345 women interviewed who received a diagnostic workup of a
Friedemann Rabe+12 more
wiley +1 more source
Three Applications of Conformal Prediction for Rating Breast Density in Mammography [PDF]
Breast cancer is the most common cancers and early detection from mammography screening is crucial in improving patient outcomes. Assessing mammographic breast density is clinically important as the denser breasts have higher risk and are more likely to occlude tumors.
arxiv
What's New? Women who are at high risk of breast cancer (BC), either because of a BRCA1/2 mutation or family history, require more aggressive screening. Here, the authors report on the clinical characteristics of the high‐risk women who developed BC during the TESTBREAST study. Of the 1108 participants, 124 (16.5%) developed breast cancer. Their median
Layla Andour+40 more
wiley +1 more source
Abstract Although most protective behaviors related to the COVID‐19 pandemic come with personal costs, they will produce the largest benefit if everybody cooperates. This study explores two interacting factors that drive cooperation in this tension between private and collective interests.
Jonas Ludwig, Fritz Strack
wiley +1 more source
Application of Artificial Intelligence in Medical Imaging: Current Status and Future Directions
The application of AI in medical imaging is driving a transformation from image recognition to disease management. Current advancements include accurate image diagnosis, encompassing lesion detection, and identification as well as disease‐based early diagnosis, progression prediction, and therapeutic efficacy assessment.
Yixin Yang, Lan Ye, Zhanhui Feng
wiley +1 more source
Case-level Breast Cancer Prediction for Real Hospital Settings [PDF]
Breast cancer prediction models for mammography assume that annotations are available for individual images or regions of interest (ROIs), and that there is a fixed number of images per patient. These assumptions do not hold in real hospital settings, where clinicians provide only a final diagnosis for the entire mammography exam (case).
arxiv
This case highlights the diagnostic challenges of cutaneous nerve entrapment syndromes, often overlooked and misdiagnosed, especially without a clear inciting injury. Through the utilization of musculoskeletal ultrasound, peripheral neuropathies can be diagnosed and treated successfully. ABSTRACT A 40‐year‐old woman presented with chronic left anterior
Jaime Dougherty+2 more
wiley +1 more source
Breast MRI to Screen Women With Extremely Dense Breasts
Women with extremely dense breasts are at a higher risk of breast cancer, and the sensitivity of mammography in this group is reduced due to the masking effect of overlapping tissue. This review examines supplemental screening methods to improve detection in this population, with a focus on MRI.
Carla Sitges, Ritse M. Mann
wiley +1 more source
Mammography Dual View Mass Correspondence [PDF]
Standard breast cancer screening involves the acquisition of two mammography X-ray projections for each breast. Typically, a comparison of both views supports the challenging task of tumor detection and localization. We introduce a deep learning, patch-based Siamese network for lesion matching in dual-view mammography.
arxiv
Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis [PDF]
Mammography-based screening has helped reduce the breast cancer mortality rate, but has also been associated with potential harms due to low specificity, leading to unnecessary exams or procedures, and low sensitivity. Digital breast tomosynthesis (DBT) improves on conventional mammography by increasing both sensitivity and specificity and is becoming ...
arxiv