AIMC Topic: Breast Neoplasms

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Efficient automated detection of mitotic cells from breast histological images using deep convolution neutral network with wavelet decomposed patches.

Computers in biology and medicine
In medical practice, the mitotic cell count from histological images acts as a proliferative marker for cancer diagnosis. Therefore, an accurate method for detecting mitotic cells in histological images is essential for cancer screening. Manual evalu...

A graph-based lesion characterization and deep embedding approach for improved computer-aided diagnosis of nonmass breast MRI lesions.

Medical image analysis
Nonmass-like enhancements are a common but diagnostically challenging finding in breast MRI. Nonmass-like lesions can be described as clusters of spatially and temporally inter-connected regions of enhancements, so they can be modeled as networks and...

Heterogeneous Domain Adaptation for IHC Classification of Breast Cancer Subtypes.

IEEE/ACM transactions on computational biology and bioinformatics
Increasingly, multiple parallel omics datasets are collected from biological samples. Integrating these datasets for classification is an open area of research. Additionally, whilst multiple datasets may be available for the training samples, future ...

Sparse Representation Over Learned Dictionaries on the Riemannian Manifold for Automated Grading of Nuclear Pleomorphism in Breast Cancer.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Breast cancer is found to be the most pervasive type of cancer among women. Computer aided detection and diagnosis of cancer at the initial stages can increase the chances of recovery and thus reduce the mortality rate through timely prognosis and ad...

A predictive model for high/low risk group according to oncotype DX recurrence score using machine learning.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Oncotype DX(ODX) is a 21-gene breast cancer recurrence score(RS) assay that aids in decision-making for chemotherapy in early-stage hormone receptor-positive(HR+)breast cancer. We developed a prediction tool using machine learning for hig...

Artificial Intelligence Using Open Source BI-RADS Data Exemplifying Potential Future Use.

Journal of the American College of Radiology : JACR
OBJECTIVES: With much hype about artificial intelligence (AI) rendering radiologists redundant, a simple radiologist-augmented AI workflow is evaluated; the premise is that inclusion of a radiologist's opinion into an AI algorithm would make the algo...

Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: False positives in digital mammography screening lead to high recall rates, resulting in unnecessary medical procedures to patients and health care costs. This study aimed to investigate the revolutionary deep learning methods to distinguish...

Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists.

Archives of pathology & laboratory medicine
CONTEXT.—: Nodal metastasis of a primary tumor influences therapy decisions for a variety of cancers. Histologic identification of tumor cells in lymph nodes can be laborious and error-prone, especially for small tumor foci.

PBMDR: A particle swarm optimization-based multifactor dimensionality reduction for the detection of multilocus interactions.

Journal of theoretical biology
Studies on multilocus interactions have mainly investigated the associations between genetic variations from the related genes and histopathological tumor characteristics in patients. However, currently, the identification and characterization of sus...

A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods...