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Comparative Analysis of Current Deep Learning Networks for Breast Lesion Segmentation in Ultrasound Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic lesion segmentation in breast ultrasound (BUS) images aids in the diagnosis of breast cancer, the most common type of cancer in women. Accurate lesion segmentation in ultrasound images is a challenging task due to speckle noise, artifacts, ...

RUBY: Natural Language Processing of French Electronic Medical Records for Breast Cancer Research.

JCO clinical cancer informatics
PURPOSE: Electronic medical records are a valuable source of information about patients' clinical status but are often free-text documents that require laborious manual review to be exploited. Techniques from computer science have been investigated, ...

Detection of live breast cancer cells in bright-field microscopy images containing white blood cells by image analysis and deep learning.

Journal of biomedical optics
SIGNIFICANCE: Circulating tumor cells (CTCs) are important biomarkers for cancer management. Isolated CTCs from blood are stained to detect and enumerate CTCs. However, the staining process is laborious and moreover makes CTCs unsuitable for drug tes...

[Robot-assisted Cardiac Surgery Council and Current Status and Future Prospect of Robotic Mitral Valve Surgery in Japan].

Kyobu geka. The Japanese journal of thoracic surgery
The Robot-assisted Cardiac Surgery Council (RACSC) was established in 2015, and consists of the members of three closely related surgical societies and associations. The RACSC conducts the review and approval of applicant surgeons and institutions. A...

Scaling multi-instance support vector machine to breast cancer detection on the BreaKHis dataset.

Bioinformatics (Oxford, England)
MOTIVATION: Breast cancer is a type of cancer that develops in breast tissues, and, after skin cancer, it is the most commonly diagnosed cancer in women in the United States. Given that an early diagnosis is imperative to prevent breast cancer progre...

Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach.

International journal of epidemiology
BACKGROUND: Machine learning-based risk prediction models may outperform traditional statistical models in large datasets with many variables, by identifying both novel predictors and the complex interactions between them. This study compared deep le...

Natural Language Processing to Identify Abnormal Breast, Lung, and Cervical Cancer Screening Test Results from Unstructured Reports to Support Timely Follow-up.

Studies in health technology and informatics
Cancer screening and timely follow-up of abnormal results can reduce mortality. One barrier to follow-up is the failure to identify abnormal results. While EHRs have coded results for certain tests, cancer screening results are often stored in free-t...

Comparison of MetaMap, cTAKES, SIFR, and ECMT to Annotate Breast Cancer Patient Summaries.

Studies in health technology and informatics
Most clinical texts including breast cancer patient summaries (BCPSs) are elaborated as narrative documents difficult to process by decision support systems. Annotators have been developed to extract the relevant content of such documents, e.g., Meta...