Colon Cancer

Integrating thermal liquid biopsy, clinical data, and mass spectrometry for early diagnosis and biomarker discovery in colorectal cancer.

Early detection of colorectal cancer is essential to improving survival, where yet current diagnosti...

An integrative multiomics random forest framework for robust biomarker discovery.

BACKGROUND: High-throughput technologies now produce a wide array of omics data, from genomic and tr...

Real-Time Characterization of Colonic Polyps: A Multicenter Prospective Study Evaluating the CAD-EYE System in Screening Colonoscopies.

BACKGROUND AND STUDY AIMS: Polypectomy-related costs could potentially be reduced through optical di...

CT-based Prediction of Visceral Pleural Invasion in Lung Adenocarcinoma ≤ 3 cm: Enhancing Deep Learning Specificity by Waiving Chest Wall Information.

BACKGROUND: Accurate preoperative prediction of visceral pleural invasion (VPI) in lung adenocarcino...

Digital horizons: Exploring the future of AI-enabled gastroenterology in the Kingdom of Saudi Arabia.

Artificial intelligence is rapidly reshaping gastroenterology through demonstrable gains in diagnost...

Machine learning using entropy-based texture features from MRI to differentiate histological subtypes of non-small cell lung cancer identified as metabolically active on PET/MRI.

Texture analysis is a foundational approach in imaging studies and demonstrates excellent diagnostic...

Development and validation of an Interpretable Machine learning model for Discriminating between benign and malignant breast cancer.

OBJECTIVE: Breast cancer prognosis depends on early detection. We developed and externally validated...

Personalized surveillance in giant congenital melanocytic nevus, including the role of AI, histopathology and MC1R genotyping: A case report.

Giant congenital melanocytic nevi (GCMN) are rare pigmented skin lesions present at birth that carry...

Validation of histopathology-based deep learning algorithms for detection of actionable non-small cell lung cancer biomarkers.

Non-small cell lung cancer (NSCLC) patient management relies on molecular analysis to determine elig...

Foundation Model-Enabled Multimodal Deep Learning for Prognostic Prediction in Colorectal Cancer with Incomplete Modalities: A Multi-Institutional Retrospective Study.

Accurate prognostic prediction for colorectal cancer is essential for optimizing personalized treatm...

Pathomics Signature for Prognosis and CA19-9 Interception in Pancreatic Ductal Adenocarcinoma: A Real-Life, Multi-Center Study.

Histopathological hematoxylin and eosin (H&E) slides contain valuable prognostic information for pan...

Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety c...

Establishment of threshold of human gut microbes and risk assessment system for colorectal cancer.

BACKGROUND: Being involved in the occurrence of colorectal cancer (CRC), gut microbes are potential ...

Computer Aided Polyp Detection Multi-center International Randomized Controlled Study with a Focus on Community Clinics: GAIN Clinical Trial.

BACKGROUND/AIMS: Computer-aided polyp detection (CADe) systems can enhance polyp detection, although...

LGDUnet: A dual-branch network for weakly supervised gland segmentation in H&E stained histopathological images.

Glandular segmentation holds significant importance in the pathological analysis of hematoxylin and ...

Radiomics profiling combined with clinical risk factors for preoperative Lymphatic Metastasis prediction in Colorectal cancer: A multicenter study.

PURPOSE: Accurate preoperative assessment of regional lymphatic metastases (LNM) is essential for ef...

Rethinking U-Net architecture in medical imaging: Advancing the efficient and interpretable UKAN-CBAM framework for colorectal polyp segmentation.

Prompt detection of colorectal polyps is essential for preventing colorectal cancer, a leading cause...

Hierarchical contextual information aggregation for polyp segmentation.

Impact of fine-grained learning rate configuration on the performance of medical image segmentation models.

Research on deep learning for medical image segmentation has shifted from single-modality networks t...

Approaches to assessing completeness of polyp resections in clinical practice: a systematic scoping review.

BACKGROUND: Protocols for standardized assessment of complete colorectal polyp resection are lacking...

Integrated Single Cell Spatial Analysis Reveals Dysregulated Basal Progenitor Cells in Ulcerative Colitis Pathogenesis: A Multi Omics Study.

BACKGROUND AND AIMS: Ulcerative colitis (UC), a chronic inflammatory bowel disease, causes persisten...