AIMC Topic: Breast Neoplasms

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Generalized Multifactor Dimensionality Reduction (GMDR) Analysis of Drug-Metabolizing Enzyme-Encoding Gene Polymorphisms may Predict Treatment Outcomes in Indian Breast Cancer Patients.

World journal of surgery
BACKGROUND: Prediction of response and toxicity of chemotherapy can help personalize the treatment and choose effective yet non-toxic treatment regimen for a breast cancer patient. Interplay of variations in various drug-metabolizing enzyme (DME)-enc...

Characterization of Architectural Distortion in Mammograms Based on Texture Analysis Using Support Vector Machine Classifier with Clinical Evaluation.

Journal of digital imaging
Architecture distortion (AD) is an important and early sign of breast cancer, but due to its subtlety, it is often missed on the screening mammograms. The objective of this study is to create a quantitative approach for texture classification of AD b...

Everolimus in heavily pretreated metastatic breast cancer: Is real world experience different?

Indian journal of cancer
BACKGROUND: Drugs targeting mammalian target of rapamycin signaling pathway have been recently approved for treatment of hormone receptor (HR) positive metastatic breast cancer (MBC). However, there is lack of real world data from India on the use of...

Structural Comparison of Gene Relevance Networks for Breast Cancer Tissues in Different Grades.

Combinatorial chemistry & high throughput screening
BACKGROUND: The breast is an important biological system of human with two distinct states, i.e. normal and tumoral. Research on breast cancer could be based on systematic modeling to contrast the system structures of these two states.

Probability Statements Extraction with Constrained Conditional Random Fields.

Studies in health technology and informatics
This paper investigates how to extract probability statements from academic medical papers. In previous work we have explored traditional classification methods which led to numerous false negatives. This current work focuses on constraining classifi...

Machine learning models in breast cancer survival prediction.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary fo...

Using Semantic Similarities and csbl.go for Analyzing Microarray Data.

Methods in molecular biology (Clifton, N.J.)
Cellular phenotypes result from the combined effect of multiple genes, and high-throughput techniques such as DNA microarrays and deep sequencing allow monitoring this genomic complexity. The large scale of the resulting data, however, creates challe...

Validation of a novel robot-assisted 3DUS system for real-time planning and guidance of breast interstitial HDR brachytherapy.

Medical physics
PURPOSE: In current clinical practice, there is no integrated 3D ultrasound (3DUS) guidance system clinically available for breast brachytherapy. In this study, the authors present a novel robot-assisted 3DUS system for real-time planning and guidanc...

Lymph Node Metastasis Status in Breast Carcinoma Can Be Predicted via Image Analysis of Tumor Histology.

Analytical and quantitative cytopathology and histopathology
OBJECTIVE: To develop a method whereby axillary lymph node (ALN) metastasis can be predicted without ALN dissection, via computational image analysis of routinely acquired tumor histology.

An Efficient Approach for Automated Mass Segmentation and Classification in Mammograms.

Journal of digital imaging
Breast cancer is becoming a leading death of women all over the world; clinical experiments demonstrate that early detection and accurate diagnosis can increase the potential of treatment. In order to improve the breast cancer diagnosis precision, th...