Colon Cancer

ConvPath: A software tool for lung adenocarcinoma digital pathological image analysis aided by a convolutional neural network.

BACKGROUND: The spatial distributions of different types of cells could reveal a cancer cell's growt...

An Early Intestinal Cancer Prediction Algorithm Based on Deep Belief Network.

The incidence of colorectal cancer (colorectal cancer, CRC) in China has increased in recent years, ...

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Colorectal polyps are known to be potential precursors to colorectal cancer, which is one of the lea...

Randomized Phase II Trial of Exercise, Metformin, or Both on Metabolic Biomarkers in Colorectal and Breast Cancer Survivors.

BACKGROUND: Observational data support inverse relationships between exercise or metformin use and d...

Computer-assisted assessment of colonic polyp histopathology using probe-based confocal laser endomicroscopy.

INTRODUCTION: Probe-based confocal laser endomicroscopy (pCLE) is a promising modality for classifyi...

Automated polyp segmentation for colonoscopy images: A method based on convolutional neural networks and ensemble learning.

PURPOSE: To automatically and efficiently segment the lesion area of the colonoscopy polyp image, a ...

Identification of genes of four malignant tumors and a novel prediction model development based on PPI data and support vector machines.

Triple-negative breast cancer (TNBC), colon adenocarcinoma (COAD), ovarian cancer (OV), and glioblas...

A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging.

BACKGROUND: To develop a supervised machine learning (ML) algorithm predicting above- versus below-m...

New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection.

Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy.

Gaps in colonoscopy skills among endoscopists, primarily due to experience, have been identified, an...

ARA: accurate, reliable and active histopathological image classification framework with Bayesian deep learning.

Machine learning algorithms hold the promise to effectively automate the analysis of histopathologic...

A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy.

PURPOSE: Development of a supervised machine-learning model capable of predicting clinically relevan...

Computer-Aided Diagnosis in Histopathological Images of the Endometrium Using a Convolutional Neural Network and Attention Mechanisms.

Uterine cancer (also known as endometrial cancer) can seriously affect the female reproductive syste...

Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images.

Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fu...

Phytochemical analysis and evaluation of the antioxidant and antiproliferative effects of Tucumã oil nanocapsules in breast adenocarcinoma cells (MCF-7).

In this work was to develop an inedited nanocapsule with tucumã oil (). The oil presents of phytoste...

A large cohort study identifying a novel prognosis prediction model for lung adenocarcinoma through machine learning strategies.

BACKGROUND: Predicting lung adenocarcinoma (LUAD) risk is crucial in determining further treatment s...

Scoring colorectal cancer risk with an artificial neural network based on self-reportable personal health data.

Colorectal cancer (CRC) is third in prevalence and mortality among all cancers in the US. Currently,...

Precision Surgical Therapy for Adenocarcinoma of the Esophagus and Esophagogastric Junction.

INTRODUCTION: To facilitate the initial clinical decision regarding whether to use esophagectomy alo...

Challenges Facing the Detection of Colonic Polyps: What Can Deep Learning Do?

Colorectal cancer (CRC) is one of the most common causes of cancer mortality in the world. The incid...

An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets.

Cancer has been one of the most threatening diseases to human health. There have been many efforts d...

CT texture analysis for the prediction of KRAS mutation status in colorectal cancer via a machine learning approach.

PURPOSE: This study aimed to investigate whether a machine learning-based computed tomography (CT) t...