Feature selection (FS) is critical for datasets with multiple variables and features, as it helps eliminate irrelevant elements, thereby improving classification accuracy. Numerous classification strategies are effective in selecting key features fro...
Accurate prediction of the likelihood of recurrence is important in the selection of postoperative treatment for patients with early-stage breast cancer. In this study, we investigated whether deep learning algorithms can predict patients' risk of re...
BACKGROUND: Maximum intensity projections (MIPs) facilitate rapid lesion detection both for contrast-enhanced (CE) and diffusion-weighted imaging (DWI) breast magnetic resonance imaging (MRI). We evaluated the feasibility of AI-based virtual CE subtr...
. To improve survival prediction for HER2-positive breast cancer by integrating histopathological, molecular, and clinical data using a multimodal transformer framework.. We propose a multimodal transformer framework for breast cancer survival predic...
INTRODUCTION: Breast cancer Mammography (MAM) screening was proven to improve survival worldwide. However, younger patients with higher breast density made MAM less effective in China. It is necessary to establish Chinese-specific effective screening...
Breast cancer remains a formidable global health challenge, emphasizing the critical importance of accurate and early diagnosis for improved patient outcomes. In recent years, machine learning, particularly deep learning, has shown substantial promis...
Epidermal growth factor receptor (EGFR) overexpression is a key oncogenic driver in breast cancer, making it an important therapeutic target. Conventional approaches for EGFR identification, including motif- and homology-based methods, often lack acc...
QUS spectral parametric imaging offers a fast and accurate method for breast lesion characterization. This study explored using deep CNNs to classify breast lesions from QUS spectral parametric images, aiming to enhance radiomics and conventional mac...
Tissue phenotypes, such as metabolic states, inflammation, and tumor properties, emerge from both molecular states and spatial cell organization. Spatial molecular assays provide an unbiased view of tissue architecture, enabling phenotype prediction....
Imaging technologies and staining based pathology are important components of common practice cancer care. Specifically, H&E imaging is standard for almost all cancer patients. Traditionally, H&E images can serve, when used by experienced trained pat...
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