AIMC Topic: Colorectal Neoplasms

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The diagnostic value of serum cysteine protease inhibitor (CST4) in colorectal cancer: a preliminary study.

BMC gastroenterology
BACKGROUND: CST4 is associated with various cancers but its diagnostic value in colorectal cancer (CRC) has not been clearly established. This study aims to further validate the diagnostic value of CST4 in colorectal cancer using random forest models...

Decision tree-based machine learning methods for identifying colorectal cancer-associated microRNA signatures and their regulatory networks.

Scientific reports
This study aimed to identify candidate diagnostic miRNAs from the serum of colorectal cancer (CRC) patients using Boruta, a wrapper-based feature selection technique, in combination with decision tree-based machine learning methods. We analyzed three...

Identification of methylation-related genes and the potential regulatory mechanism of SLAMF6 in CMS4 colorectal cancer.

Clinical epigenetics
BACKGROUNDS: Consensus molecular subtype 4 (CMS4) of colorectal cancer (CRC) is characterized by TGF-β activation, and generally accompanied with metastasis and recurrence. Nevertheless, molecular biomarkers and regulatory mechanisms underlying CMS4 ...

Harnessing gut microbiota for colorectal cancer therapy: from clinical insights to therapeutic innovations.

NPJ biofilms and microbiomes
Colorectal cancer (CRC) remains a leading cause of cancer morbidity and mortality worldwide, yet improvements in survival have been modest despite advances in conventional therapies. The gut microbiota has emerged as a critical player in CRC pathogen...

Mapping the knowledge landscape of robotic colorectal cancer surgery: a visualization study.

Journal of robotic surgery
Robotic surgery has now been widely applied in the treatment of colorectal cancer (CRC), driving significant growth in related research activities. This study aims to reveal the research hotspots, emerging frontiers, and future research trends in the...

Multi-omics based consensus subtypes, development of prognostic signature, and identification of INHBB as a potential therapeutic target in colorectal cancer.

Functional & integrative genomics
This study aims to refine molecular subtypes via multi-omics data, develop a prognostic signature, and identify novel biomarkers in colorectal cancer (CRC). On the basis of the multi-omics data, the MOVICS R package was used to divide patients with C...

Construction of a predictive model for the risk of moderate-to-severe cancer-related fatigue in colorectal cancer chemotherapy patients: an interpretable machine learning approach.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
PURPOSE: This study aimed to analyze the influencing factors of moderate-to-severe cancer-related fatigue (CRF) in colorectal cancer (CRC) chemotherapy patients and to develop a predictive risk stratification model.

The Cost-Effectiveness of AI-Assisted Colonoscopy as a Primary or Secondary Screening Test in a Population-Based Colorectal Cancer Screening Program: Markov Modeling-Based Cost Effectiveness Analysis.

Journal of medical Internet research
BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide and poses a heavy burden on health care systems. Early screening for CRC through colonoscopy can effectively reduce both the incidence and mortality associated with CRC. Ho...

Adjacent-differential network with shallow attention for polyp segmentation in colonoscopy images.

Scientific reports
Colonoscopy is the gold standard for the examination and detection of polyps, with over 90% of polyps potentially progressing into colorectal cancer. Accurate polyp segmentation plays a pivotal role in the early diagnosis and treatment of colorectal ...

Graph neural networks learn emergent tissue properties from spatial molecular profiles.

Nature communications
Tissue phenotypes, such as metabolic states, inflammation, and tumor properties, emerge from both molecular states and spatial cell organization. Spatial molecular assays provide an unbiased view of tissue architecture, enabling phenotype prediction....