IEEE journal of biomedical and health informatics
Mar 6, 2025
Accurate breast tumor segmentation in ultrasound images is a crucial step in medical diagnosis and locating the tumor region. However, segmentation faces numerous challenges due to the complexity of ultrasound images, similar intensity distributions,...
In breast diagnostic imaging, the morphological variability of breast tumors and the inherent ambiguity of ultrasound images pose significant challenges. Moreover, multi-task computer-aided diagnosis systems in breast imaging may overlook inherent re...
Neural networks : the official journal of the International Neural Network Society
Mar 4, 2025
Given the rapid increase in breast cancer incidence, the Automated Breast Volume Scanner (ABVS) is developed to screen breast tumours efficiently and accurately. However, reviewing ABVS images is a challenging task owing to the significant variations...
Breast cancer remains a global health burden, with an increase in deaths related to this particular cancer. Accurately predicting and diagnosing breast cancer is important for treatment development and survival of patients. This study aimed to accura...
Biomedical physics & engineering express
Mar 4, 2025
Despite significant progress in diagnosis and treatment, breast cancer remains a formidable health challenge, emphasizing the continuous need for research. This simulation study uses polarized Monte Carlo approach to identify and locate breast cancer...
Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
Mar 4, 2025
BACKGROUND AND OBJECTIVES: Prior studies have shown that small non-coding RNAs (sncRNAs) are associated with cancer occurrence or development. Recently, a newly discovered class of small ncRNAs known as PIWI-interacting RNAs (piRNAs) have been found ...
Predicting low nuclear grade DCIS before surgery can improve treatment choices and patient care, thereby reducing unnecessary treatment. Due to the high heterogeneity of DCIS and the limitations of biopsies in fully characterizing tumors, current dia...
Current breast cancer diagnosis methods often face limitations such as high cost, time consumption, and inter-observer variability. To address these challenges, this research proposes a novel deep learning framework that leverages generative adversar...
The Artificial Intelligence Patient Librarian (AIPL) was designed to meet the psychosocial and supportive care needs of Metastatic Breast Cancer (MBC) patients with HR+/HER2- subtypes. AIPL provides conversational patient education, answers user ques...
Breast reconstruction following mastectomy or sectorectomy significantly impacts the quality of life and psychological well-being of breast cancer patients. Since its inception in the 1950s, artificial intelligence (AI) has gradually entered the medi...