International journal of colorectal disease
Jun 16, 2022
PURPOSE: Evidence regarding local recurrence rates in the initial cases after implementation of robot-assisted total mesorectal excision is limited. This study aims to describe local recurrence rates in four large Dutch centres during their initial c...
OBJECTIVE: To investigate the clinical safety and efficacy of a modified early unclamping technique in robot-assisted laparoscopic partial nephrectomy (RAPN).
Computer methods and programs in biomedicine
May 25, 2022
BACKGROUND AND OBJECTIVE: Adjuvant chemotherapy is recommended as standard treatment for colorectal cancer (CRC) with stage III according to TNM stage. However, outcomes are varied even among patients receiving similar treatments. We aimed to develop...
European journal of nuclear medicine and molecular imaging
Apr 26, 2022
PURPOSE: How to discriminate different risks of recurrent nasopharyngeal carcinoma (rNPC) patients and guide individual treatment has become of great importance. This study aimed to explore the associations between deep learning signatures and biolog...
OBJECTIVES: This preliminary study aimed to develop a deep learning (DL) model using diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps to predict local recurrence and 2-year progression-free survival (PFS) in laryngeal an...
In radiation oncology, predicting patient risk stratification allows specialization of therapy intensification as well as selecting between systemic and regional treatments, all of which helps to improve patient outcome and quality of life. Deep lear...
Risk evaluation of lymph node metastasis (LNM) for endoscopically resected submucosal invasive (T1) colorectal cancers (CRC) is critical for determining therapeutic strategies, but interobserver variability for histologic evaluation remains a major p...
Long noncoding RNAs (lncRNAs) are recently implicated in modifying immunology in colorectal cancer (CRC). Nevertheless, the clinical significance of immune-related lncRNAs remains largely unexplored. In this study, we develope a machine learning-base...