Colon Cancer

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 colonoscopy. We evaluated the impact of a novel artificial intelligence (AI) system, compared with standard high-definition colonoscopy, for APC measurement.

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

BACKGROUND: Colon microbiome composition contributes to the pathogenesis of colorectal cancer (CRC) and prognosis. We analyzed 16S rRNA sequencing data from tumor samples of patients with metastatic CRC and determined the clinical implications.

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 cancer (CRC). However, the criteria for selecting...

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 pathology, leading to the development of automated ...

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 diseases. Many computer-aided systems have been deve...

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 metastasis (OLNM) is pivotal for determining treatment str...

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 EGFR genotyping is crucial for optimal treatment ou...

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, lymphovascular invasion, tumour grade, perineural i...

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 generating accurate reports. While recent studies ha...

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 colorectal cancer incidence. Both linked-color imaging (...

Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes.

It is poorly understood how different cells in a tissue organize themselves to support tissue functions. We describe the CytoCommunity algorithm for t...

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 composition has not been routinely integrated into trea...

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 malignancies. However, current methods for CD276 detection a...

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 data exists concerning these patients and their outco...

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 adenocarcinoma (LUAD), and preoperative knowledge of STA...

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, genetic subtypes, and mutations associated with CR...

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 intelligence (AI) in the course of endoscopic procedures can ...

Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework.

Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was to identify promising biomarkers for LUAD. Using th...

Deep learning system for true- and pseudo-invasion in colorectal polyps.

Over 15 million colonoscopies were performed yearly in North America, during which biopsies were taken for pathological examination to identify abnorm...

From Staining Techniques to Artificial Intelligence: A Review of Colorectal Polyps Characterization.

This review article provides a comprehensive overview of the evolving techniques in image-enhanced endoscopy (IEE) for the characterization of colorec...