AIMC Topic: Breast Neoplasms

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Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance.

European radiology Aug 12, 2021
OBJECTIVES: To evaluate if artificial intelligence (AI) can discriminate recalled benign from recalled malignant mammographic screening abnormalities to improve screening performance.
Female Breast Neoplasms Deep Learning Humans Artificial Intelligence Retrospective Studies Negotiating Mass Screening Early Detection of Cancer Mammography
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Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence-Based Computer-Aided Detection.

AJR. American journal of roentgenology Aug 11, 2021
Postoperative mammograms present interpretive challenges due to postoperative distortion and hematomas. The application of digital breast tomosyn-thesis (DBT) and artificial intelligence-based computer-aided detection (AI-CAD) after breast-conservin...
Humans Artificial Intelligence Retrospective Studies Middle Aged Mammography Radiographic Image Interpretation, Computer-Assisted Mastectomy, Segmental Breast Neoplasm Recurrence, Local Young Adult Adult Breast Neoplasms Female Aged Aged, 80 and over
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Radiomics Analysis Based on Automatic Image Segmentation of DCE-MRI for Predicting Triple-Negative and Nontriple-Negative Breast Cancer.

Computational and mathematical methods in medicine Aug 10, 2021
PURPOSE: To investigate whether quantitative radiomics features extracted from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) could be used to differentiate triple-negative breast cancer (TNBC) and nontriple-negative breast cancer (no...
Breast Neoplasms Principal Component Analysis ROC Curve Humans China Triple Negative Breast Neoplasms Middle Aged Computational Biology Female Image Interpretation, Computer-Assisted Software Contrast Media Deep Learning Cohort Studies Retrospective Studies Aged Magnetic Resonance Imaging Adult
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GATNNCDA: A Method Based on Graph Attention Network and Multi-Layer Neural Network for Predicting circRNA-Disease Associations.

International journal of molecular sciences Aug 7, 2021
Circular RNAs (circRNAs) are a new class of endogenous non-coding RNAs with covalent closed loop structure. Researchers have revealed that circRNAs play an important role in human diseases. As experimental identification of interactions between circR...
Female Breast Neoplasms Humans Neural Networks, Computer Liver Neoplasms RNA, Circular Carcinoma, Hepatocellular Computational Biology Databases, Nucleic Acid RNA, Neoplasm
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Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning.

Computers in biology and medicine Aug 5, 2021
When doctors use contrast-enhanced computed tomography (CECT) images to predict the metastasis of axillary lymph nodes (ALN) for breast cancer patients, the prediction performance could be degraded by subjective factors such as experience, psychologi...
Retrospective Studies Tomography, X-Ray Computed Female Lymph Nodes Lymphatic Metastasis Humans Breast Neoplasms Deep Learning
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Predicting chronic pain in postoperative breast cancer patients with multiple machine learning and deep learning models.

Journal of clinical anesthesia Aug 4, 2021
Deep Learning Humans Machine Learning Postoperative Period Female Chronic Pain Breast Neoplasms
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Deep Learning Based Capsule Neural Network Model for Breast Cancer Diagnosis Using Mammogram Images.

Interdisciplinary sciences, computational life sciences Aug 2, 2021
Breast cancer is a commonly occurring disease in women all over the world. Mammogram is an efficient technique used for screening and identification of abnormalities over the breast region. Earlier identification of breast cancer enhances the prognos...
Humans Breast Neoplasms Deep Learning Mammography Breast Neural Networks, Computer Algorithms Female
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A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images.

JAMA network open Aug 2, 2021
IMPORTANCE: Breast cancer screening is among the most common radiological tasks, with more than 39 million examinations performed each year. While it has been among the most studied medical imaging applications of artificial intelligence, the develop...
Datasets as Topic Female False Positive Reactions Reproducibility of Results Early Detection of Cancer Aged Mammography Deep Learning Breast Humans ROC Curve Breast Neoplasms Middle Aged
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AI-enhanced breast imaging: Where are we and where are we heading?

European journal of radiology Jul 30, 2021
Significant advances in imaging analysis and the development of high-throughput methods that can extract and correlate multiple imaging parameters with different clinical outcomes have led to a new direction in medical research. Radiomics and artific...
Image Processing, Computer-Assisted Humans Mammography Artificial Intelligence Breast Female Breast Neoplasms
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Efficacy of da Vinci robot-assisted lymph node surgery than conventional axillary lymph node dissection in breast cancer - A comparative study.

The international journal of medical robotics + computer assisted surgery : MRCAS Jul 29, 2021
BACKGROUND: da Vinci robot-assisted axillary lymph node dissection (dVALND) can be a minimally invasive technique to minimize post-operative complications.
Robotics Robotic Surgical Procedures Mastectomy Lymph Nodes Lymphatic Metastasis Lymph Node Excision Female Breast Neoplasms Quality of Life Humans
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