Colon Cancer

Hyperspectral Image Analysis of Colon Tissue and Deep Learning for Characterization of Health care.

Colon cancer is a disease characterized by the unusual and uncontrolled development of cells that ar...

Integration of Transcriptomics and Metabolomics Reveals the Antitumor Mechanism Underlying Tadalafil in Colorectal Cancer.

The potential role of tadalafil, a PDE5 inhibitor, in anticancer activity and prolonged survival has...

Deep learning with whole slide images can improve the prognostic risk stratification with stage III colorectal cancer.

BACKGROUND AND OBJECTIVE: Adjuvant chemotherapy is recommended as standard treatment for colorectal ...

Diagnosis of Nonperitonealized Colorectal Cancer with Computerized Tomography Image Features under Deep Learning.

This study aimed to explore the value of abdominal computerized tomography (CT) three-dimensional re...

Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response.

High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformati...

A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Evaluation of KRAS Mutation in Rectal Cancer.

BACKGROUND: Recent studies showed the potential of MRI-based deep learning (DL) for assessing treatm...

Calf Thymus Polypeptide Restrains the Growth of Colorectal Tumor Regulating the Intestinal Microbiota-Mediated Immune Function.

Calf thymus polypeptide (CTP), with a molecular mass of <10 kDa, is prepared from the thymus of less...

Editorial for "A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Prediction of KRAS Mutation in Rectal Cancer".

Special issue "The advance of solid tumor research in China": Prognosis prediction for stage II colorectal cancer by fusing computed tomography radiomics and deep-learning features of primary lesions and peripheral lymph nodes.

Currently, the prognosis assessment of stage II colorectal cancer (CRC) remains a difficult clinical...

Polyp segmentation network with hybrid channel-spatial attention and pyramid global context guided feature fusion.

In clinical practice, automatic polyp segmentation from colonoscopy images is an effective assistant...

Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions.

BACKGROUND: The efficiency of artificial intelligence as computer-aided detection (CADe) systems for...

Auxiliary Diagnosis of Lung Cancer with Magnetic Resonance Imaging Data under Deep Learning.

This study was aimed at two image segmentation methods of three-dimensional (3D) U-shaped network (U...

Artificial Intelligence Improves Detection at Colonoscopy: Why Aren't We All Already Using It?

Short-term results of robot-assisted colorectal cancer surgery using Senhance Digital Laparoscopy System.

BACKGROUND: The Senhance Digital Laparoscopy System (Asensus Surgical Inc, Morrisville, NC, United S...

Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma.

This study aimed to explore the prognostic impact of spatial distribution of tumor-infiltrating lymp...

Swarm learning for decentralized artificial intelligence in cancer histopathology.

Artificial intelligence (AI) can predict the presence of molecular alterations directly from routine...

Artificial intelligence to identify genetic alterations in conventional histopathology.

Precision oncology relies on the identification of targetable molecular alterations in tumor tissues...

Detection and Classification of Colorectal Polyp Using Deep Learning.

Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by d...

Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa.

Real-Time Artificial Intelligence-Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy.

BACKGROUND: Artificial intelligence using computer-aided diagnosis (CADx) in real time with images a...

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study.

BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colo...