Breast cancer is the second most common cancer worldwide, primarily affecting women, while histopathological image analysis is one of the possibile methods used to determine tumor malignancy. Regarding image analysis, the application of deep learning...
Journal of the Egyptian National Cancer Institute
Jun 10, 2024
BACKGROUND: The goal is to use three different machine learning models to predict the recurrence of breast cancer across a very heterogeneous sample of patients with varying disease kinds and stages.
PURPOSE: This study aims to assess the diagnostic value of ultrasound habitat sub-region radiomics feature parameters using a fully connected neural networks (FCNN) combination method L2,1-norm in relation to breast cancer Ki-67 status.
PURPOSE: To conduct the fusion of radiomics and deep transfer learning features from the intratumoral and peritumoral areas in breast DCE-MRI images to differentiate between benign and malignant breast tumors, and to compare the diagnostic accuracy o...
PURPOSE: Artificial intelligence (AI) for reading breast screening mammograms could potentially replace (some) human-reading and improve screening effectiveness. This systematic review aims to identify and quantify the types of AI errors to better un...
Journal of magnetic resonance imaging : JMRI
Jun 8, 2024
BACKGROUND: Pathological complete response (pCR) is an essential criterion for adjusting follow-up treatment plans for patients with breast cancer (BC). The value of the visual geometry group and long short-term memory (VGG-LSTM) network using time-s...
BACKGROUND: Breast cancer is the most common cancer among women, and ultrasound is a usual tool for early screening. Nowadays, deep learning technique is applied as an auxiliary tool to provide the predictive results for doctors to decide whether to ...
INTRODUCTION: Artificial intelligence (AI)-driven chatbots, capable of simulating human-like conversations, are becoming more prevalent in healthcare. While this technology offers potential benefits in patient engagement and information accessibility...
- This paper presents a comprehensive study focused on breast cancer subtyping, utilizing a multifaceted approach that integrates feature selection, machine learning classifiers, and miRNA regulatory networks. The feature selection process begins wit...