Colon Cancer

A USP15/KRT17-associated 13-gene prognostic cluster and functional validation in EGFR-mutant lung adenocarcinoma.

BACKGROUND: EGFR-mutant lung adenocarcinoma (LUAD) exhibits significant prognostic heterogeneity despite the efficacy of tyrosine kinase inhibitors. To uncover the transcriptomic markers of rapid disease progression, we integrated clinical and transcriptomic data to develop robust prognostic biomarkers for risk stratification. METHODS: We utilized ensemble machine learning algorithms, including Ra...

Next-generation precision oncology in microsatellite stable colorectal cancer: integrated targeting beyond RAS and RAF.

The therapeutic landscape of colorectal cancer (CRC) has evolved with the identification of molecular subtypes, including mismatch repair-deficient/microsatellite instability-high, POLE mutations, RAS/BRAF alterations, and HER2 amplification, enabling use of precision therapies and immune checkpoint inhibitors for selected populations. However, most microsatellite-stable (MSS) tumors remain resist...

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer scr...

Human-artificial intelligence adaptation in colonoscopy: beyond deskilling and upskilling.

A Multimodal Deep Learning Model for Preoperative Prediction of Postoperative Complications in Gastric Cancer.

BACKGROUND: Clavien-Dindo (CD) grade ≥II complications occur in roughly one in five patients after curative gastrectomy for gastric cancer and indepen...

MoCaPS: a machine learning model for stratification of cancer-associated cachexia based on blood biomarkers.

Identification of minimally invasive biomarkers of cancer-associated cachexia may help to recognize high risk patients for progression to more severe ...

An efficient framework for real-time colorectal polyp detection using local outlier factor-based preprocessing and YOLOv11n.

Timely and accurate detection of colorectal polyps plays an important role in the prevention and early diagnosis of colorectal cancer. Despite the adv...

Circulating multi-omic signature of disease severity and cholangiocarcinoma in primary sclerosing cholangitis.

BACKGROUND: Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease often associated with inflammatory bowel disease (IBD) that ca...

BiCervi: Pap smear microscopy image dataset for cervical cancer detection and classification.

Cervical cancer is still a major public-health challenge, especially in low and middle-income countries where there are limited numbers of specialists...

Deep Learning Predicts Imminent Tumor Progression in Advanced Pancreatic Adenocarcinoma Using Serial CT Scans During Chemotherapy.

Advanced pancreatic ductal adenocarcinoma (PDAC) often progresses rapidly during chemotherapy despite initial assessments of stable disease or partial...

Functionally Guided Graph Learning for Robust Cross-Patient Cell-Type Annotation in Single-Cell RNA Sequencing.

Cross-patient cell-type annotation in single-cell RNA sequencing (scRNA-seq) remains challenging due to pronounced interpatient heterogeneity and dist...

AI-driven multi-omics deciphering of extrachromosomal circular DNA rescues hidden targets in colorectal cancer.

BACKGROUND: Extrachromosomal circular DNA (eccDNA) is an emerging tumor biomarker notable for its tumor-specific amplification and contribution to gen...

Identifying Potential Exosome-Derived mRNA Biomarkers for Diagnosis and Prediction of Breast Cancer Using Machine-Learning Approaches.

INTRODUCTION: Breast cancer remains a major global health burden, underscoring the urgent need for reliable early detection strategies. Exosomes, as m...

Clinical Study on the Prevention of High-Risk Pulmonary Nodule Progression With Yifei Sanjie Pill: Protocol for a Multicenter Randomized Controlled Trial.

BACKGROUND: High-risk subsolid pulmonary nodules, especially mixed ground-glass nodules, can represent precancerous or early-stage lung adenocarcinoma...

An explainable multimodal 2.5D deep learning-radiomics model for predicting extranodal extension in lung adenocarcinoma using preoperative CT: a multicenter retrospective cohort study.

OBJECTIVE: This study aimed to develop the Radiomics-Assembled ENE system (RAIEm), a multimodal preoperative computed tomography (CT) radiomics model,...

Novel plasma protein signatures for early diagnosis and prognostic stratification in colorectal cancer.

Colorectal cancer (CRC) remains a major global health concern, underscoring the need for reliable biomarkers for diagnosis and prognosis. In this stud...

MRI-based radiomics interpretable model predicts microsatellite instability status in endometrioid adenocarcinoma.

OBJECTIVE: To develop and validate a multiparametric MRI-based radiomics model for noninvasive preoperative prediction of microsatellite instability (...

Automated model-based lesion tracking in CT: colorectal liver metastases as a use case for development and performance analysis.

OBJECTIVE: To develop and evaluate an automated CT liver lesion-tracking algorithm that matches lesions over time, detects new metastases, and reports...

Use of an AI Image Recognition-Based Smartphone App in Personalized Bowel Preparation Before Colonoscopy: Prospective Randomized Controlled Trial.

BACKGROUND: Sufficient bowel preparation is critical for increasing the quality of colonoscopy. However, current bowel preparation guidelines have lim...

Improving preoperative risk stratification in colorectal liver metastases: a multi-institutional evaluation of multimodal prediction models.

Reliable prognostic models of death or liver recurrence following resection of colorectal liver metastases are critical to stratify patients for treat...