AIMC Topic: Breast Neoplasms

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Accuracy and efficiency of an artificial intelligence tool when counting breast mitoses.

Diagnostic pathology Jul 4, 2020
BACKGROUND: The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately substantial inter- and intra-laboratory variation exists when pathologists manually count mitotic figures. Artificial intelligence (AI) coupled with wh...
Deep Learning Humans Image Processing, Computer-Assisted Female Breast Neoplasms Carcinoma, Ductal, Breast Mitotic Index
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A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning.

Scientific reports Jul 2, 2020
Response to Neoadjuvant chemotherapy (NAC) has demonstrated a high correlation to survival in locally advanced breast cancer (LABC) patients. An early prediction of responsiveness to NAC could facilitate treatment adjustments on an individual patient...
Humans Middle Aged Machine Learning Adolescent Prognosis Aged Tomography, X-Ray Computed ROC Curve Carcinoma, Ductal, Breast Aged, 80 and over Female Receptors, Progesterone Neoadjuvant Therapy Antineoplastic Combined Chemotherapy Protocols Receptors, Estrogen Young Adult Carcinoma, Lobular Follow-Up Studies Adult Breast Neoplasms Receptor, ErbB-2
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Challenge for Diagnostic Assessment of Deep Learning Algorithm for Metastases Classification in Sentinel Lymph Nodes on Frozen Tissue Section Digital Slides in Women with Breast Cancer.

Cancer research and treatment Jun 30, 2020
PURPOSE: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of SLNs by a pathologist is not easy and is a tedious and...
Sentinel Lymph Node Aged Adult Aged, 80 and over Humans Breast Neoplasms Sentinel Lymph Node Biopsy Image Processing, Computer-Assisted Middle Aged Predictive Value of Tests Frozen Sections Republic of Korea Lymphatic Metastasis Deep Learning Female Neoplasm Staging ROC Curve
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A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI.

Scientific reports Jun 29, 2020
Multiparametric magnetic resonance imaging (mpMRI) has been shown to improve radiologists' performance in the clinical diagnosis of breast cancer. This machine learning study develops a deep transfer learning computer-aided diagnosis (CADx) methodolo...
Middle Aged Multiparametric Magnetic Resonance Imaging Breast Humans Aged Diagnosis, Computer-Assisted Retrospective Studies Image Interpretation, Computer-Assisted Deep Learning Adult Female Breast Neoplasms
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Computational inference of cancer-specific vulnerabilities in clinical samples.

Genome biology Jun 29, 2020
BACKGROUND: Systematic in vitro loss-of-function screens provide valuable resources that can facilitate the discovery of drugs targeting cancer vulnerabilities.
Computational Biology Computer Simulation Models, Biological Breast Neoplasms Humans Molecular Targeted Therapy Deep Learning Point Mutation
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Virtual Interpolation Images of Tumor Development and Growth on Breast Ultrasound Image Synthesis With Deep Convolutional Generative Adversarial Networks.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine Jun 27, 2020
OBJECTIVES: We sought to generate realistic synthetic breast ultrasound images and express virtual interpolation images of tumors using a deep convolutional generative adversarial network (DCGAN).
Female Breast Neoplasms Ultrasonography, Mammary Growth and Development Neural Networks, Computer Humans Retrospective Studies
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Role of artificial intelligence and vibrational spectroscopy in cancer diagnostics.

Expert review of molecular diagnostics Jun 27, 2020
INTRODUCTION: Raman and Infrared spectroscopic techniques are being used for the analysis of different types of cancers and other biological molecules. It is possible to identify cancers from normal tissues both in fresh and fixed tissues. These tech...
Humans Neural Networks, Computer Breast Neoplasms Neoplasms Spectrum Analysis, Raman Spectrum Analysis Artificial Intelligence Machine Learning Female
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Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density.

Journal of the American College of Radiology : JACR Jun 24, 2020
OBJECTIVE: We developed deep learning algorithms to automatically assess BI-RADS breast density.
Female Breast Neoplasms Breast Density Humans Deep Learning Artificial Intelligence Mammography Crowdsourcing
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Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations.

British journal of cancer Jun 22, 2020
BACKGROUND: The clinical utility of machine-learning (ML) algorithms for breast cancer risk prediction and screening practices is unknown. We compared classification of lifetime breast cancer risk based on ML and the BOADICEA model. We explored the d...
Early Detection of Cancer Risk Adult Breast Neoplasms Middle Aged Humans Machine Learning Aged Young Adult Retrospective Studies Female
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Integrating spatial gene expression and breast tumour morphology via deep learning.

Nature biomedical engineering Jun 22, 2020
Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial resolution, making it possible to systematically link the morphology of cellular neighbourhoods and spatially localized gene expression. Here, we report the develop...
Image Processing, Computer-Assisted Gene Expression Profiling Transcriptome Deep Learning Reproducibility of Results Breast Neoplasms Biomarkers, Tumor Algorithms Female Humans
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