The lancet. Gastroenterology & hepatology
Aug 14, 2024
BACKGROUND: Increased polyp detection during colonoscopy is associated with decreased post-colonoscopy colorectal cancer incidence and mortality. The COLO-DETECT trial aimed to assess the clinical effectiveness of the GI Genius intelligent endoscopy ...
BACKGROUND: Early detection and treatment of colorectal cancer (CRC) is crucial for improving patient survival rates. This study aims to identify signature molecules associated with CRC, which can serve as valuable indicators for clinical hematologic...
BACKGROUND: In patients with primary and secondary liver cancer, the number and sizes of lesions, their locations within the Couinaud segments, and the volume and health status of the future liver remnant are key for informing treatment planning. Cur...
Tumorigenesis and treatment are closely associated with various programmed cell death (PCD) patterns. However, the coregulatory role of multiple PCD patterns in colorectal cancer (CRC) remains unknown. In this study, we developed a multiple PCD index...
BMC medical informatics and decision making
Aug 8, 2024
OBJECTIVE: To develop a machine learning-based risk prediction model for postoperative parastomal hernia (PSH) in colorectal cancer patients undergoing permanent colostomy, assisting nurses in identifying high-risk groups and devising preventive care...
Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and tumor microenvironment (TME) variability. Intra-tumor heterogeneity and its connections with metabolic reprogramming an...
Early and accurate detection of colorectal cancer (CRC) is critical for improving patient outcomes. Existing diagnostic techniques are often invasive and carry risks of complications. Herein, we introduce a plasmonic gold nanopolyhedron (AuNH)-coated...
GOALS: To develop an automated method for Adenoma Detection Rate (ADR) calculation and report card generation using common electronic health records (EHRs).
OBJECTIVE: To develop and externally validate an updated artificial intelligence (AI) prediction system for stratifying the risk of lymph node metastasis (LNM) in T2 colorectal cancer (CRC).
Colorectal liver metastasis (CRLM) is challenging in the clinical treatment of colorectal cancer. Limited research has been conducted on how CRLM develops. RNA sequencing data were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome...
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