AIMC Topic: Breast Neoplasms

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Deep Learning Radiomics of Preoperative Breast MRI for Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

Journal of digital imaging
The objective of this study is to develop a radiomic signature constructed from deep learning features and a nomogram for prediction of axillary lymph node metastasis (ALNM) in breast cancer patients. Preoperative magnetic resonance imaging data from...

Deep learning neural network image analysis of immunohistochemical protein expression reveals a significantly reduced expression of biglycan in breast cancer.

PloS one
New breast cancer biomarkers have been sought for better tumor characterization and treatment. Among these putative markers, there is Biglycan (BGN). BGN is a class I small leucine-rich proteoglycan family of proteins characterized by a protein core ...

Deep Learning With an Attention Mechanism for Differentiating the Origin of Brain Metastasis Using MR images.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Brain metastasis (BM) is a serious neurological complication of cancer of different origins. The value of deep learning (DL) to identify multiple types of primary origins remains unclear.

Breast Tumor Classification using Short-ResNet with Pixel-based Tumor Probability Map in Ultrasound Images.

Ultrasonic imaging
Breast cancer is the most common form of cancer and is still the second leading cause of death for women in the world. Early detection and treatment of breast cancer can reduce mortality rates. Breast ultrasound is always used to detect and diagnose ...

Multi CNN based automatic detection of mitotic nuclei in breast histopathological images.

Computers in biology and medicine
In breast cancer diagnosis, the number of mitotic cells in a specific area is an important measure. It indicates how far the tumour has spread, which has consequences for forecasting the aggressiveness of cancer. Mitosis counting is a time-consuming ...

Deep Learning-Based Segmentation of Locally Advanced Breast Cancer on MRI in Relation to Residual Cancer Burden: A Multi-Institutional Cohort Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: While several methods have been proposed for automated assessment of breast-cancer response to neoadjuvant chemotherapy on breast MRI, limited information is available about their performance across multiple institutions.

Geometric and dosimetric evaluation of deep learning based auto-segmentation for clinical target volume on breast cancer.

Journal of applied clinical medical physics
BACKGROUND: Recently, target auto-segmentation techniques based on deep learning (DL) have shown promising results. However, inaccurate target delineation will directly affect the treatment planning dose distribution and the effect of subsequent radi...

CustOmics: A versatile deep-learning based strategy for multi-omics integration.

PLoS computational biology
The availability of patient cohorts with several types of omics data opens new perspectives for exploring the disease's underlying biological processes and developing predictive models. It also comes with new challenges in computational biology in te...

A novel survival prediction signature outperforms PAM50 and artificial intelligence-based feature-selection methods.

Computational biology and chemistry
The robustness of a breast cancer gene signature, the super-proliferation set (SPS), is initially tested and investigated on breast cancer cell lines from the Cancer Cell Line Encyclopaedia (CCLE). Previously, SPS was derived via a meta-analysis of 4...