AIMC Topic: Breast Neoplasms

Clear Filters Showing 1911 to 1920 of 2382 articles

An Open-architecture AI Model for CPT Coding in Breast Surgery: Development, Validation, and Prospective Testing.

Annals of surgery
OBJECTIVE: To develop, validate, and prospectively test an open-architecture, transformer-based artificial Intelligence (AI) model to extract procedure codes from free-text breast surgery operative notes.

Effects of concurrent HER2-directed therapy on development of cerebral radionecrosis after stereotactic radiotherapy: a systematic review.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PURPOSE: With increasing use of human epithelial growth factor receptor two (HER2)-targeted therapies, outcomes for numerous breast cancer patients have improved. Nevertheless, patients with HER2-positive tumours face a comparatively heightened risk ...

Spatial discovery of pyrotinib overcoming HER2-positive breast cancer resistance by breaking fibroblast-induced immune barriers.

Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy
BACKGROUND: The TCbHP regimen, consisting of combining docetaxel (T), carboplatin (Cb), trastuzumab (H), and pertuzumab (P), is the preferred neoadjuvant treatment for locally advanced human epidermal growth factor 2 (HER2)-positive breast cancer. Ho...

Improving Breast Cancer Diagnosis in Ultrasound Images Using Deep Learning with Feature Fusion and Attention Mechanism.

Academic radiology
RATIONALE AND OBJECTIVES: Early detection of malignant lesions in ultrasound images is crucial for effective cancer diagnosis and treatment. While traditional methods rely on radiologists, deep learning models can improve accuracy, reduce errors, and...

Role of machine learning in molecular pathology for breast cancer: A review on gene expression profiling and RNA sequencing application.

Critical reviews in oncology/hematology
INTRODUCTION: Breast cancer is the most prevalent cancer among women, with growing incidence and mortality rates. Regardless of remarkable progress in cancer research, breast cancer remains a major concern due to its complex nature. These factors und...

Assessing the quality of Japanese online breast cancer treatment information using large language models: a comparison of ChatGPT, Claude, and expert evaluations.

Breast cancer (Tokyo, Japan)
BACKGROUND: The internet is a primary source of health information for breast cancer patients, but online content quality varies widely. This study aimed to evaluate the capability of large language models (LLMs), including ChatGPT and Claude, to ass...

[Comparison of diagnostic performance between artificial intelligence-assisted automated breast ultrasound and handheld ultrasound in breast cancer screening].

Zhonghua yi xue za zhi
To compare the diagnostic performance of artificial intelligence-assisted automated breast ultrasound (AI-ABUS) with traditional handheld ultrasound (HHUS) in breast cancer screening. A total of 36 171 women undergoing breast cancer ultrasound scre...

Using Machine Learning to Improve Control for Confounding in the Dynamic Weighted Ordinary Least Squares Estimator of Optimal Adaptive Treatment Strategies.

Biometrical journal. Biometrische Zeitschrift
Estimating optimal adaptive treatment strategies (ATSs) can be done in several ways, including dynamic weighted ordinary least squares (dWOLS). This approach is doubly robust as it requires modeling both the treatment and the response, but only one o...

Self-Supervised Optimization of RF Data Coherence for Improving Breast Reflection UCT Reconstruction.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The reflection ultrasound computed tomography (UCT) is gaining prominence as an essential instrument for breast cancer screening. However, reflection UCT quality is often compromised by the variability in sound speed across breast tissue. Traditional...