Latest AI and machine learning research in breast cancer for healthcare professionals.
INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) undergoing stereotactic body radiation therapy (SBRT) develop metastases, which is associated with poor outcomes. We sought to identify factors predictive of metastases after lung SBRT and created a risk stratification tool.
PURPOSE: The purpose of this study was to compare the effectiveness of ensemble methods (e.g., random forests) and single-model methods (e.g., logistic regression and decision trees) in predictive modeling of post-RT treatment failure and adverse events (AEs) for breast cancer patients using automatically extracted EMR data.
PURPOSE: In multiphase coronary CT angiography (CTA), a series of CT images are taken at different levels of radiation dose during the examination. Al...
OBJECTIVE: To report our initial experience and short-term results in post-chemotherapy robot-assisted retroperitoneal lymph node dissection (RA-RPLND...
OBJECTIVE: Although CT has been used as a complementary diagnostic method for the preoperative diagnosis of thyroid cancer, it has the shortcomings of...
BACKGROUND: We applied machine learning to find a novel breast cancer predictor based on information in a mammogram.
Natured botanical extract has attracted considerable attention recently in the field of skin anti-ultraviolet (UV) radiation. As a medicinal herb, Sop...
OBJECTIVEIntravertebral augmentation (IVA) is a reliable minimally invasive technique for treating Magerl type A vertebral body fractures. However, po...
Positron emission tomography (PET) has been substantially used recently. To minimize the potential health risk caused by the tracer radiation inherent...
PURPOSE: Patients with head-and-neck cancer (HNC) may experience xerostomia after radiation therapy (RT), which leads to compromised quality of life. ...
Worldwide, the standard treatment for locally advanced esophageal cancer with curative intent is perioperative chemotherapy or preoperative chemoradio...
PURPOSE: Sparsely sampled computed tomography (CT) has been attracting attention as a technique that can reduce the high radiation dose of conventiona...
PURPOSE: Quantitative changes in positron emission tomography with computed tomography imaging metrics over serial scans may be predictive biomarkers....
Introduction Dose reductions are often required to avoid toxicity in combination therapy for advanced cancers, but information on appropriate dose red...
BACKGROUND: African American (AA) individuals are less likely to receive treatment and more likely to die from cancer compared with Caucasian (C) indi...
The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b)...
To assess the accuracy and time requirements of image-guided percutaneous K-wire insertion in the spine using an advanced robot assistance device for...
PURPOSE: Breast cancer (BC) is the most common cancer in women worldwide. There exist various advanced chemotherapy drugs for BC; however, chemotherap...
Convolutional neural network (CNN) type artificial intelligences were trained to estimate the Cerenkov radiation present in the temporal response of a...
INTRODUCTION: This is a retrospective study conducted to report the tumor control and late toxicity outcomes of patients with intermediate-risk prosta...