AIMC Topic: Breast Neoplasms

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Deep computational pathology in breast cancer.

Seminars in cancer biology
Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-world datasets for cross-domain and cross-discipline prediction and classification tasks. DL architectures excel in computer vision tasks, and in particular ...

New convolutional neural network model for screening and diagnosis of mammograms.

PloS one
Breast cancer is the most common cancer in women and poses a great threat to women's life and health. Mammography is an effective method for the diagnosis of breast cancer, but the results are largely limited by the clinical experience of radiologist...

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage.

PloS one
BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can detect precancerous cells and allow for earlier diagnosis and treatment. Our purpose was to better understand risk factors for cancer screenings and a...

Artificial Intelligence in plastic surgery: What is it? Where are we now? What is on the horizon?

Annals of the Royal College of Surgeons of England
INTRODUCTION: An increasing quantity of data is required to guide precision medicine and advance future healthcare practices, but current analytical methods often become overwhelmed. Artificial intelligence (AI) provides a promising solution. Plastic...

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Methods (San Diego, Calif.)
Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovarian cancer patients can facilitate the therapeutics evaluation and treatment decision making. Multi-...

Breast Cancer Histopathology Image Classification Using an Ensemble of Deep Learning Models.

Sensors (Basel, Switzerland)
Breast cancer is one of the major public health issues and is considered a leading cause of cancer-related deaths among women worldwide. Its early diagnosis can effectively help in increasing the chances of survival rate. To this end, biopsy is usual...

Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Breast cancer is a frequently diagnosed cancer in women, contributing to significant mortality rates. Death rates are relatively higher in developing nations due to the shortage of early detection amenities and constraints o...

Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.

Genes
With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between various subtypes, so as to infer the underlying mechanisms. Given the available multi-omics data, their proper integration can improve the accuracy o...

Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges.

Journal of infection and public health
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of pathological changes. Cancerous cells are abnormal areas often growing in any part of human body that are life-threatening. Cancer also known as tumor must be qui...

Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information.

Asian Pacific journal of cancer prevention : APJCP
PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information.