Colon Cancer

Accurate diagnosis of colorectal cancer based on histopathology images using artificial intelligence.

BACKGROUND: Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is...

Outcomes and complications of patients undergoing Salter's innominate osteotomies for hip dysplasia: a systematic review of comparative studies.

The purpose of this systematic review is to assess outcomes and complications of patients undergoing...

Preoperative prediction of regional lymph node metastasis of colorectal cancer based on F-FDG PET/CT and machine learning.

PURPOSE: To establish and validate a regional lymph node (LN) metastasis prediction model of colorec...

Deep learning detects genetic alterations in cancer histology generated by adversarial networks.

Deep learning can detect microsatellite instability (MSI) from routine histology images in colorecta...

Deep learning-based tumor microenvironment analysis in colon adenocarcinoma histopathological whole-slide images.

BACKGROUND AND OBJECTIVE: Colon cancer is a fatal disease, and a comprehensive understanding of the ...

A new rapid diagnostic system with ambient mass spectrometry and machine learning for colorectal liver metastasis.

BACKGROUND: Probe electrospray ionization-mass spectrometry (PESI-MS) can rapidly visualize mass spe...

Deep learning classification of lung cancer histology using CT images.

Tumor histology is an important predictor of therapeutic response and outcomes in lung cancer. Tissu...

A robust electrochemical immunosensor based on core-shell nanostructured silica-coated silver for cancer (carcinoembryonic-antigen-CEA) diagnosis.

This work addresses the fabrication of an efficient, novel, and economically viable immunosensing ar...

A novel method to objectively assess robotic assistance in laparoscopic colorectal surgery.

OBJECTIVE: An objective assessment of robotic assistance in colorectal surgery.

State of the art in robotic rectal surgery: marginal gains worth the pain?

After their first introduction in the 1990s to overcome the limitations of conventional laparoscopic...

Prediction of the histology of colorectal neoplasm in white light colonoscopic images using deep learning algorithms.

The treatment plan of colorectal neoplasm differs based on histology. Although new endoscopic imagin...

Generation of Dual functional Nanobody-Nanoluciferase Fusion and its potential in Bioluminescence Enzyme Immunoassay for trace Glypican-3 in Serum.

Glypican-3 (GPC3) is a serological biomarker for the diagnosis of Hepatocellular carcinoma (HCC), bu...

Artificial intelligence for colonoscopy: the new Silk Road.

Establishment and clinical application value of an automatic diagnosis platform for rectal cancer T-staging based on a deep neural network.

BACKGROUND: Colorectal cancer is harmful to the patient's life. The treatment of patients is determi...

Machine Learning-based Differentiation of Benign and Premalignant Colorectal Polyps Detected with CT Colonography in an Asymptomatic Screening Population: A Proof-of-Concept Study.

Background CT colonography does not enable definite differentiation between benign and premalignant ...

Computational learning of features for automated colonic polyp classification.

Shape, texture, and color are critical features for assessing the degree of dysplasia in colonic pol...

Colorectal polyp characterization with standard endoscopy: Will Artificial Intelligence succeed where human eyes failed?

The American Society for Gastrointestinal Endoscopy (ASGE) has proposed the "resect-and-discard" and...

Deep-learning system for real-time differentiation between Crohn's disease, intestinal Behçet's disease, and intestinal tuberculosis.

BACKGROUND AND AIM: Pattern analysis of big data can provide a superior direction for the clinical d...

An annotation-free whole-slide training approach to pathological classification of lung cancer types using deep learning.

Deep learning for digital pathology is hindered by the extremely high spatial resolution of whole-sl...

A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution.

Colon carcinoma is one of the leading causes of cancer-related death in both men and women. Automati...

A novel machine learning-based algorithm to identify and classify lesions and anatomical landmarks in colonoscopy images.

OBJECTIVES: Computer-aided diagnosis (CAD)-based artificial intelligence (AI) has been shown to be h...