The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety concerns during the learning curve, particularly when complex cases are preferentially selected for the robotic platform. We evaluated a machine learni...
PURPOSE: Accurate preoperative assessment of regional lymphatic metastases (LNM) is essential for effective surgical selection of patients with colorectal cancer (CRC). This study aimed to develop a machine learning (ML) model that integrates radiomi...
Medical oncology (Northwood, London, England)
Jan 13, 2026
Recent advances in Medical Oncology highlight the integration of bulk and single-cell transcriptomics to reveal glycolytic heterogeneity in colorectal cancer. Translating these discoveries into reliable clinical tools requires rigorous methods, trans...
International journal of colorectal disease
Jan 9, 2026
OBJECTIVE: To develop and validate machine learning models based on preoperative magnetic resonance imaging(MRI) and baseline clinical characteristics for predicting early recurrence(ER) in patients with colorectal liver metastases(CRLM) treated with...
INTRODUCTION: After curative treatment for colorectal cancer (CRC), there is a 15% risk of recurrence. Early detection of an asymptomatic recurrence may lead to curative treatment options. To date, follow-up strategies do not have optimal sensitivity...
Biomedical physics & engineering express
Jan 5, 2026
Accurate detection and segmentation of polyps during colonoscopy are of great significance for the early prevention and treatment of colorectal cancer. However, due to the considerable variations in polyp size and shape, as well as their blurred boun...
The simultaneous determination of the expression levels of multiple inflammation-associated cytokines in blood holds great promise for the early screening of cancer including colorectal cancer (CRC). Herein, an antibody microarray-based sandwich meta...
Single-molecule detection (SMD) holds considerable promise in biomedical research. Although atomic force microscopy (AFM) provides an important technique with nanoscale resolution for SMD, its broader application is limited by labeling challenges and...
High-precision pixel-level annotation has been a major bottleneck in computational pathology due to its time-consuming nature and reliance on expert knowledge. Semi-supervised learning (SSL) provides a promising approach to alleviate this challenge b...
Automated segmentation of colorectal polyps is of great significance for early screening and clinical intervention of colorectal cancer. However, the diversity of polyp morphology and the uneven contrast caused by illumination changes in colonoscopy ...
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