AIMC Topic: Breast Neoplasms

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Glycotherapy: A New Paradigm in Breast Cancer Research.

Biomolecules
Breast cancer is an ancient disease recognized first by the Egyptians as early as 1600 BC. The first cancer-causing gene in a chicken tumor virus was found in 1970. The United States signed the National Cancer Act in 1971, authorizing federal funding...

Predicting Breast Cancer Based on Optimized Deep Learning Approach.

Computational intelligence and neuroscience
Breast cancer is a dangerous disease with a high morbidity and mortality rate. One of the most important aspects in breast cancer treatment is getting an accurate diagnosis. Machine-learning (ML) and deep learning techniques can help doctors in makin...

Classification of breast cancer with deep learning from noisy images using wavelet transform.

Biomedizinische Technik. Biomedical engineering
In this study, breast cancer classification as benign or malignant was made using images obtained by histopathological procedures, one of the medical imaging techniques. First of all, different noise types and several intensities were added to the im...

Deep learning method with a convolutional neural network for image classification of normal and metastatic axillary lymph nodes on breast ultrasonography.

Japanese journal of radiology
PURPOSE: To investigate the ability of deep learning (DL) using convolutional neural networks (CNNs) for distinguishing between normal and metastatic axillary lymph nodes on ultrasound images by comparing the diagnostic performance of radiologists.

An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions.

European radiology
OBJECTIVES: To build an artificial intelligence (AI) system to classify benign and malignant non-mass enhancement (NME) lesions using maximum intensity projection (MIP) of early post-contrast subtracted breast MR images.

Application of a Deep-Learning Technique to Non-Linear Images From Human Tissue Biopsies for Shedding New Light on Breast Cancer Diagnosis.

IEEE journal of biomedical and health informatics
The development of label-free non-destructive techniques to be used as diagnostic tools in cancer research is of great importance for improving the quality of life for millions of patients. Previous studies have demonstrated that Third Harmonic Gener...

Breast cancer detection using artificial intelligence techniques: A systematic literature review.

Artificial intelligence in medicine
Cancer is one of the most dangerous diseases to humans, and yet no permanent cure has been developed for it. Breast cancer is one of the most common cancer types. According to the National Breast Cancer Foundation, in 2020 alone, more than 276,000 ne...

Artificial intelligence for histological subtype classification of breast cancer: combining multi-scale feature maps and the recurrent attention model.

Histopathology
AIMS: The aim of this study was to apply a two-stage deep model combining multi-scale feature maps and the recurrent attention model (RAM) to assist with the pathological diagnosis of breast cancer histological subtypes by the use of whole slide imag...

Detection of Breast Cancer Using Histopathological Image Classification Dataset with Deep Learning Techniques.

BioMed research international
Cancer is one of the top causes of mortality, and it arises when cells in the body grow abnormally, like in the case of breast cancer. For people all around the world, it has now become a huge issue and a threat to their safety and wellbeing. Breast ...

Tomographic Ultrasound Imaging in the Diagnosis of Breast Tumors under the Guidance of Deep Learning Algorithms.

Computational intelligence and neuroscience
This study was aimed to discuss the feasibility of distinguishing benign and malignant breast tumors under the tomographic ultrasound imaging (TUI) of deep learning algorithm. The deep learning algorithm was used to segment the images, and 120 patien...