Technology in cancer research & treatment
Jan 1, 2024
To establish a model based on clinical and delta-radiomic features within ultrasound images using XGBoost machine learning to predict proliferation-associated nuclear antigen Ki-67 value ≥ 15% in TNM stage primary breast cancer (BC). Data were coll...
BACKGROUND/AIM: Overall survival (OS)-predictive models to clinically stratify patients with stage I Non-Small Cell Lung Cancer (NSCLC) undergoing stereotactic body radiation therapy (SBRT) are still unavailable. The aim of this work was to build a p...
Shanghai kou qiang yi xue = Shanghai journal of stomatology
Oct 1, 2023
PURPOSE: To investigate the efficacy and prognostic factors of oral robot-assisted retropharyngeal lymph node (RPLN) dissection in the treatment of head and neck malignancies.
INTRODUCTION: Prostate cancer (PCa) is a disease with a high prevalence and incidence worldwide. Screening has pursued the early diagnosis of this disease to provide early treatment. We sought to characterize patients from a local hospital with respe...
Robotic lobectomy volume in the United States has increased dramatically in the past 10 years. Improved perioperative outcomes and increased public demand for minimally invasive techniques continue to drive its popularity. Preoperative workup is simi...
PURPOSE OF REVIEW: Robot-assisted laparoscopic staging (RALS) is increasingly used for staging epithelial ovarian cancer (EOC). Evidence of its safety is limited. The aim of this review is to compare the efficacy and safety of RALS in clinical early-...
Colorectal cancer lymph node metastasis, which is highly associated with the patient's cancer recurrence and survival rate, has been the focus of many therapeutic strategies that are highly associated with the patient's cancer recurrence and survival...
OBJECTIVE: We aimed to develop a deep learning-based signature to predict prognosis and benefit from adjuvant chemotherapy using preoperative computed tomography (CT) images.
Detecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel noninvasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise predictions with low-depth cfDN...
BACKGROUND: To assess the additive value of dual-energy CT (DECT) over single-energy CT (SECT) to radiomics-based response prediction in patients with metastatic melanoma preceding immunotherapy.