AI Medical Compendium Journal:
Breast cancer research and treatment

Showing 11 to 20 of 24 articles

Deep learning-guided adjuvant chemotherapy selection for elderly patients with breast cancer.

Breast cancer research and treatment
PURPOSE: The efficacy of adjuvant chemotherapy in elderly breast cancer patients is currently controversial. This study aims to provide personalized adjuvant chemotherapy recommendations using deep learning (DL).

Classification of breast tumors by using a novel approach based on deep learning methods and feature selection.

Breast cancer research and treatment
PURPOSE: Cancer is one of the most insidious diseases that the most important factor in overcoming the cancer is early diagnosis and detection. The histo-pathological images are used to determine whether the tissue is cancerous and the type of cancer...

Early experience of robotic axillary lymph node dissection in patients with node-positive breast cancer.

Breast cancer research and treatment
BACKGROUND: Robotic surgical systems enable surgeons to perform precise movement in the surgical field using high-resolution 3D vision and flexible robotic instruments. We aimed to evaluate the feasibility and safety of performing axillary lymph node...

Multiparametric radiomics methods for breast cancer tissue characterization using radiological imaging.

Breast cancer research and treatment
BACKGROUND AND PURPOSE: Multiparametric radiological imaging is vital for detection, characterization, and diagnosis of many different diseases. Radiomics provide quantitative metrics from radiological imaging that may infer potential biological mean...

Breast cancer outcome prediction with tumour tissue images and machine learning.

Breast cancer research and treatment
PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.

Machine learning for diagnostic ultrasound of triple-negative breast cancer.

Breast cancer research and treatment
PURPOSE: Early diagnosis of triple-negative (TN) breast cancer is important due to its aggressive biological characteristics, poor clinical outcomes, and limited options for therapy. The goal of this study is to evaluate the potential of machine lear...

Prediction of postoperative disease-free survival and brain metastasis for HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab using a machine learning algorithm.

Breast cancer research and treatment
PURPOSE: This study aimed to develop mathematical tools to predict the likelihood of recurrence after neoadjuvant chemotherapy (NAC) plus trastuzumab in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer.

Machine-learning-derived classifier predicts absence of persistent pain after breast cancer surgery with high accuracy.

Breast cancer research and treatment
BACKGROUND: Prevention of persistent pain following breast cancer surgery, via early identification of patients at high risk, is a clinical need. Supervised machine-learning was used to identify parameters that predict persistence of significant pain...