AIMC Topic: Breast Neoplasms

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HRProfiler Detects Homologous Recombination Deficiency in Breast and Ovarian Cancers Using Whole-Genome and Whole-Exome Sequencing Data.

Cancer research
UNLABELLED: Breast and ovarian cancers harboring homologous recombination deficiency (HRD) are sensitive to PARP inhibitors and platinum chemotherapy. Conventionally, detecting HRD involves screening for defects in BRCA1, BRCA2, and other relevant ge...

Enhancing nuclei segmentation in breast histopathology images using U-Net with backbone architectures.

Computers in biology and medicine
Breast cancer remains a leading cause of mortality among women worldwide, underscoring the need for accurate and timely diagnostic methods. Precise segmentation of nuclei in breast histopathology images is crucial for effective diagnosis and prognosi...

Computational modeling of breast tissue mechanics and machine learning in cancer diagnostics: enhancing precision in risk prediction and therapeutic strategies.

Expert review of anticancer therapy
INTRODUCTION: Breast cancer remains a significant global health issue. Despite advances in detection and treatment, its complexity is driven by genetic, environmental, and structural factors. Computational methods like Finite Element Modeling (FEM) h...

A review of explainable AI techniques and their evaluation in mammography for breast cancer screening.

Clinical imaging
Explainable AI (XAI) methods are gaining prominence in medical imaging, addressing the critical need for transparency and trust in AI-driven diagnostic tools. Mammography, as the cornerstone of early breast cancer detection, holds immense potential f...

Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors.

Breast cancer research and treatment
PURPOSE: Noninvasive, accurate and novel approaches to predict patients who will achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) could assist treatment strategies. The aim of this study was to explore the application...

A deep learning framework for reconstructing Breast Amide Proton Transfer weighted imaging sequences from sparse frequency offsets to dense frequency offsets.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Amide Proton Transfer (APT) technique is a novel functional MRI technique that enables quantification of protein metabolism, but its wide application is largely limited in clinical settings by its long acquisition time. One way to reduce the scanning...

Multi-task learning for joint prediction of breast cancer histological indicators in dynamic contrast-enhanced magnetic resonance imaging.

Computer methods and programs in biomedicine
OBJECTIVES: Achieving efficient analysis of multiple pathological indicators has great significance for breast cancer prognosis and therapeutic decision-making. In this study, we aim to explore a deep multi-task learning (MTL) framework for collabora...

ABVS breast tumour segmentation via integrating CNN with dilated sampling self-attention and feature interaction Transformer.

Neural networks : the official journal of the International Neural Network Society
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...

Wearable device for axillary lymph node screening in breast cancer based on infrared thermography and artificial intelligence.

Breast cancer research : BCR
BACKGROUND: Breast cancer (BC) is the most prevalent cancer among women worldwide, and patients with metastasis to axillary lymph nodes (ALN) experience significantly lower survival rates. Current imaging-based screening methods often suffer from low...

Scientific hypothesis generation by large language models: laboratory validation in breast cancer treatment.

Journal of the Royal Society, Interface
Large language models (LLMs) have transformed artificial intelligence (AI) and achieved breakthrough performance on a wide range of tasks. In science, the most interesting application of LLMs is for hypothesis formation. A feature of LLMs, which resu...