Colon Cancer

Predictive value of artificial intelligence-based quantitative CT feature analysis for diagnosing the pathological types of pulmonary nodules.

OBJECTIVES: Accurate preoperative classification of pulmonary nodules (PNs) is critical for guiding ...

What can we learn about chronic rhinosinusitis through mucus?

PURPOSE OF REVIEW: Sinonasal mucus biomarkers have emerged as a powerful, noninvasive tool to better...

Artificial intelligence for colorectal polyp sizing: clinical promise and methodological challenges.

Impact of artificial intelligence-assisted colonoscopy on gastroenterology fellow performance: a pragmatic randomized controlled trial.

BACKGROUND AND AIMS: The substantial miss rate during screening and surveillance colonoscopy, partic...

AI for colon cancer: A focus on classification, detection, and predictive modeling.

PURPOSE: Artificial Intelligence (AI) is increasingly recognized for its potential in improving the ...

Radiomics-based artificial intelligence (AI) models in colorectal cancer (CRC) diagnosis, metastasis detection, prognosis, and treatment response prediction.

Colorectal cancer (CRC) is the third most common cause of cancer-related morbidity and mortality in ...

Refining the Classroom: The Self-Supervised Professor Model for Improved Segmentation of Locally Advanced Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related deaths, with accurate s...

HAMIL: Hierarchical Attention Multi-Instance Learning for Label-Free Colorectal Cancer Typing.

Colorectal cancer (CRC) is one of the leading gastrointestinal malignancies, underscoring the need f...

ToBaFu: Topology-based fusion model for classification of two-dimensional cancer images.

Medical images play a pivotal role in disease diagnosis. Numerous studies on cancer image analysis f...

Integration of machine learning and SERS technology for precise classification and diagnosis of colon cancer from plasma samples.

Surface-Enhanced Raman Spectroscopy (SERS) combined with machine learning offers a transformative la...

Clinical implications of computer-aided real-time size estimation of colorectal polyps during colonoscopy: a prospective study.

Accurate polyp size estimation during colonoscopy is crucial for clinical decision making, follow-up...

Colorectal mucosal exposure area assessment using artificial intelligence: a multicenter prospective observational study.

This study proposed a new quality control indicator for colonoscopy, the cumulative colorectal mucos...

Identifying meaningful drug response biomarkers from public pharmacogenomic datasets with biologically informed interpretable neural networks.

With the advancements of next-generation sequencing, publicly available pharmacogenomic datasets fro...

Screening for Barrett Esophagus and Esophageal Adenocarcinoma: Approaches and Outcomes.

Barrett esophagus (BE) is the only known histological precursor to esophageal adenocarcinoma (EAC). ...

Artificial Intelligence for Quantifying Endoscopic Mucosal Ulceration in Crohn's Disease.

BACKGROUND & AIMS: Endoscopic scoring of Crohn's disease (CD) is challenging, as mucosal disease is ...

Determining the Survival Impact and Cost-Effectiveness of Multi-Gene Panel Sequencing in Metastatic Colorectal Cancer With Super Learning Approaches.

OBJECTIVE: To determine the effectiveness and cost-effectiveness of multi-gene panel sequencing comp...

Efficacy of artificial intelligence for adenoma detection in water exchange colonoscopy: a two-center randomized controlled trial.

Water exchange and artificial intelligence-based computer-aided detection (CADe) separately improve ...

Machine learning pipeline with custom grid search for colorectal Raman spectroscopy data.

Colorectal cancer remains a major health burden, and its early detection is crucial for effective tr...

Artificial Intelligence and Endoscopist Diagnostic Agreement as a Framework for Colorectal Polyp Optical Diagnosis Implementation.

Intestinal therapeutic agent delivery microrobot with magnetic targeting and pH-triggered degradation abilities.

Oral drug delivery remains a clinically preferred route for colorectal cancer therapy due to its non...

Colon cancer survival prediction from gland shapes within histology slides using deep learning.

This study investigates the application of deep learning techniques for segmenting glands in histopa...