Breast cancer dominates women's mortality, and among other factors, mutations in the BRCA1 gene are significant risk factors. Several approaches are followed to treat the BRCA1 affected cancer patients. However, specific BRCA1 inhibitors are not avai...
BACKGROUND: Artificial intelligence (AI) chatbots, including ChatGPT-4 (GPT-4) and Grok-1 (Grok), have been shown to be potentially useful in several medical fields, but have not been examined in plastic and aesthetic surgery. The aim of this study i...
PURPOSE: There are many radiological datasets for breast cancer, some which have supported the development of AI medical devices for breast cancer screening and image classification. This review aims to identify mammography datasets (including digiti...
Early diagnosis and treatment of breast cancer can effectively reduce mortality. Since mammogram is one of the most commonly used methods in the early diagnosis of breast cancer, the classification of mammogram images is an important work of computer...
Collagen, a key structural component of the extracellular matrix, undergoes significant remodeling during carcinogenesis. However, the important role of collagen levels in breast cancer diagnostics still lacks effective in vivo detection techniques t...
This study explores the integration of Raman spectroscopy (RS) with machine learning for the early detection and subtyping of breast cancer using blood plasma samples. We performed detailed spectral analyses, identifying significant spectral patterns...
Interdisciplinary sciences, computational life sciences
Nov 22, 2024
Gene Regulatory Networks (GRNs) reveal complex interactions between genes in organisms, crucial for understanding the life system's operation. The rapid development of biotechnology, especially single-cell RNA sequencing (scRNA-seq), has generated a ...
BACKGROUND: Recent healthcare advancements highlight the potential of Artificial Intelligence (AI) - and especially, among its subfields, Machine Learning (ML) - in enhancing Breast Cancer (BC) clinical care, leading to improved patient outcomes and ...
PURPOSE: Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling is useful in predicting pathologic complete response (pCR) to NAC. We test machine learning (ML) models to predict pCR in breast cancer and explore met...
BACKGROUND: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the urgent need for innovative prognostic tools to improve treatment strategies. Anoikis, a form of programmed cell death critical in preventing metasta...
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