Colon Cancer

Use of Artificial Intelligence in Lower Gastrointestinal and Small Bowel Disorders: An Update Beyond Polyp Detection.

Machine learning and its specialized forms, such as Artificial Neural Networks and Convolutional Neural Networks, are increasingly being used for detecting and managing gastrointestinal conditions. Recent advancements involve using Artificial Neural Network models to enhance predictive accuracy for severe lower gastrointestinal (LGI) bleeding outcomes, including the need for surgery. To this end, ...

NLP for Analyzing Electronic Health Records and Clinical Notes in Cancer Research: A Review.

This review examines the application of natural language processing (NLP) techniques in cancer research using electronic health records (EHRs) and clinical notes. It addresses gaps in existing literature by providing a broader perspective than previous studies focused on specific cancer types or applications. A comprehensive literature search in the Scopus database identified 94 relevant studies p...

Multiscale deep learning radiomics for predicting recurrence-free survival in pancreatic cancer: A multicenter study.

PURPOSE: This multicenter study aimed to develop and validate a multiscale deep learning radiomics nomogram for predicting recurrence-free survival (R...

Identification of therapeutic targets for Alzheimer's Disease Treatment using bioinformatics and machine learning.

Alzheimer's disease (AD) is a complex neurodegenerative disorder that currently lacks effective treatment options. This study aimed to identify potent...

Tumor Cellularity Assessment Using Artificial Intelligence Trained on Immunohistochemistry-Restained Slides Improves Selection of Lung Adenocarcinoma Samples for Molecular Testing.

Tumor cellularity (TC) in lung adenocarcinoma slides submitted for molecular testing is important in identifying actionable mutations, but lack of bes...

Interpretable multi-stage attention network to predict cancer subtype, microsatellite instability, TP53 mutation and TMB of endometrial and colorectal cancer.

Mismatch repair deficiency (dMMR), also known as high-grade microsatellite instability (MSI-H), is a well-established biomarker for predicting the imm...

Super-resolution deep-learning reconstruction with 1024 matrix improves CT image quality for pancreatic ductal adenocarcinoma assessment.

OBJECTIVES: To evaluate the efficiency of super-resolution deep-learning reconstruction (SR-DLR) optimized for helical body imaging in assessing pancr...

Integrating multiomics analysis and machine learning to refine the molecular subtyping and prognostic analysis of stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly precise treatment options. We downloaded the multiom...

A Machine Learning Approach Using Topic Modeling to Identify and Assess Experiences of Patients With Colorectal Cancer: Explorative Study.

BACKGROUND: The rising number of cancer survivors and the shortage of health care professionals challenge the accessibility of cancer care. Health tec...

Artificial Intelligence in Pancreatic Imaging: A Systematic Review.

The rising incidence of pancreatic diseases, including acute and chronic pancreatitis and various pancreatic neoplasms, poses a significant global hea...

Effect of artificial intelligence-aided differentiation of adenomatous and non-adenomatous colorectal polyps at CT colonography on radiologists' therapy management.

OBJECTIVES: Adenomatous colorectal polyps require endoscopic resection, as opposed to non-adenomatous hyperplastic colorectal polyps. This study aims ...

Single-cell RNA sequencing and machine learning provide candidate drugs against drug-tolerant persister cells in colorectal cancer.

Drug resistance often stems from drug-tolerant persister (DTP) cells in cancer. These cells arise from various lineages and exhibit complex dynamics. ...

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.

The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate bot...

Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.

To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular typing and prognosis prediction in lung adenocarcin...

Immunolipid magnetic bead-based circulating tumor cell sorting: a novel approach for pathological staging of colorectal cancer.

OBJECTIVE: This study aimed to assess whether circulating tumor cells (CTCs) from colorectal cancer (CRC) could be used as an alternative to tissue sa...

A comparative analysis and survival analysis of open versus minimally invasive radical antegrade modular pancreatosplenectomy for pancreatic cancer: a systematic review and meta-analysis.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a major public health concern, ranking as the fourth leading cause of cancer-related mortality ...

An Artificial Intelligence-Digital Pathology Algorithm Predicts Survival After Radical Prostatectomy From the Prostate, Lung, Colorectal, and Ovarian Cancer Trial.

PURPOSE: Clinical variables alone have limited ability to determine which patients will have recurrence after radical prostatectomy (RP). We evaluated...

PEDRA-EFB0: colorectal cancer prognostication using deep learning with patch embeddings and dual residual attention.

In computer-aided diagnosis systems, precise feature extraction from CT scans of colorectal cancer using deep learning is essential for effective prog...

Machine learning classification and biochemical characteristics in the real-time diagnosis of gastric adenocarcinoma using Raman spectroscopy.

This study aimed to identify biomolecular differences between benign gastric tissues (gastritis/intestinal metaplasia) and gastric adenocarcinoma and ...

Impact of Artificial Intelligence on Gastroenterology Trainee Education.

Artificial intelligence (AI) is transforming gastroenterology, particularly in endoscopy, which has a direct impact on trainees and their education. A...