Latest AI and machine learning research in breast cancer for healthcare professionals.
BACKGROUND: Automatic segmentation and localization of lesions in mammogram (MG) images are challeng...
The hypothesis that destructive mass extinctions enable creative evolutionary radiations (creative d...
INTRODUCTION: While the long-term oncologic safety of robot-assisted nipple sparing mastectomy (RNSM...
This study aimed to investigate the predictive efficacy of positron emission tomography/computed tom...
OBJECTIVE: Breast cancer is the most common malignancy among women and often requires surgery for th...
PURPOSE: The purpose of this study was to develop and validate a deep learning (DL)-based radiomics ...
The prevalence of cancer as a threat to human life, responsible for 9.6 million deaths worldwide in ...
Acute esophagitis (AE) occurs among a significant number of patients with locally advanced lung canc...
STUDY OBJECTIVE: Compare survival of patients with advanced epithelial ovarian cancer (EOC) undergoi...
Innovations in CT have been impressive among imaging and medical technologies in both the hardware a...
Background CT deep learning reconstruction (DLR) algorithms have been developed to remove image nois...
Non-invasive ischemic cancer therapy requires reduced blood flow whereas drug delivery and radiation...
PURPOSE: Contouring inconsistencies are known but understudied in clinical radiation therapy trials....
PURPOSE: This study investigated deep learning models for automatic segmentation to support the deve...
Systemic chemotherapy remains the backbone of many cancer treatments. Due to its untargeted nature a...
Positron emission tomography (PET) imaging plays an indispensable role in early disease detection an...
IMPORTANCE: Postoperative chemoradiation is the standard of care for cancers with positive margins o...
The American Cancer Society expected to diagnose 276,480 new cases of invasive breast cancer in the ...
PURPOSE: This work aims to study the generalizability of a pre-developed deep learning (DL) dose pre...
PURPOSE: To develop a deep learning model that generates consistent, high-quality lymph node clinica...
BACKGROUND: To use clinical and MRI radiomic features coupled with machine learning to assess HER2 e...