Colon Cancer

Integrating clinical and cross-cohort metagenomic features: a stable and non-invasive colorectal cancer and adenoma diagnostic model.

Dysbiosis is associated with colorectal cancer (CRC) and adenomas (CRA). However, the robustness of...

Machine Learning Developed a MYC Expression Feature-Based Signature for Predicting Prognosis and Chemoresistance in Pancreatic Adenocarcinoma.

MYC has been identified to profoundly influence a wide range of pathologic processes in cancers. How...

Predicting 5-year recurrence risk in colorectal cancer: development and validation of a histology-based deep learning approach.

BACKGROUND: Accurate estimation of the long-term risk of recurrence in patients with non-metastatic ...

A Framework for the Evaluation of Human Machine Interfaces of Robot-Assisted Colonoscopy.

UNLABELLED: The Human Machine Interface (HMI) of intraluminal robots has a crucial impact on the cli...

Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.

INTRODUCTION: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colo...

Robotic transanal minimally invasive repair of a colorectal anastomosis leak-a video vignette.

High-accuracy prediction of colorectal cancer chemotherapy efficacy using machine learning applied to gene expression data.

FOLFOX and FOLFIRI chemotherapy are considered standard first-line treatment options for colorectal...

Tumor-associated microbiome features of metastatic colorectal cancer and clinical implications.

BACKGROUND: Colon microbiome composition contributes to the pathogenesis of colorectal cancer (CRC) ...

Histopathology image classification: highlighting the gap between manual analysis and AI automation.

The field of histopathological image analysis has evolved significantly with the advent of digital p...

Two-stage deep-learning-based colonoscopy polyp detection incorporating fisheye and reflection correction.

BACKGROUND AND AIM: Colonoscopy is a useful method for the diagnosis and management of colorectal di...

Predicting occult lymph node metastasis in solid-predominantly invasive lung adenocarcinoma across multiple centers using radiomics-deep learning fusion model.

BACKGROUND: In solid-predominantly invasive lung adenocarcinoma (SPILAC), occult lymph node metastas...

Using Vision Transformer for high robustness and generalization in predicting EGFR mutation status in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma is a common cause of cancer-related deaths worldwide, and accurate E...

Lymph node metastases and recurrence in pT1 colorectal cancer: Prediction with the International Budding Consortium Score-A retrospective, multi-centric study.

BACKGROUND: The International Collaboration on Cancer Reporting proposes histological tumour type, l...

Density clustering-based automatic anatomical section recognition in colonoscopy video using deep learning.

Recognizing anatomical sections during colonoscopy is crucial for diagnosing colonic diseases and ge...

Linked-color imaging with or without artificial intelligence for adenoma detection: a randomized trial.

BACKGROUND: Adenoma detection rate (ADR) is an important indicator of colonoscopy quality and colore...

Prognostic value of deep learning-derived body composition in advanced pancreatic cancer-a retrospective multicenter study.

BACKGROUND: Despite the prognostic relevance of cachexia in pancreatic cancer, individual body compo...

Management and outcomes of brain metastases from pancreatic adenocarcinoma: a pooled analysis and literature review.

BACKGROUND: Brain metastases (BM) are rare in pancreatic ductal adenocarcinoma (PDAC) and little dat...

Establishment of a pathomic-based machine learning model to predict CD276 (B7-H3) expression in colon cancer.

CD276 is a promising prognostic indicator and an attractive therapeutic target in various malignanci...

CT-Based Super-Resolution Deep Learning Models with Attention Mechanisms for Predicting Spread Through Air Spaces of Solid or Part-Solid Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: Spread through air space (STAS) is a novel invasive pattern of lung adenoc...

Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer.

Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, ...

Efficacy of artificial intelligence in reducing miss rates of GI adenomas, polyps, and sessile serrated lesions: a meta-analysis of randomized controlled trials.

BACKGROUND AND AIMS: The aim of this study was to determine if utilization of artificial intelligenc...