Colon Cancer

Deep learning radiomics model related with genomics phenotypes for lymph node metastasis prediction in colorectal cancer.

BACKGROUND AND PURPOSE: The preoperative lymph node (LN) status is important for the treatment of co...

Real-time automated diagnosis of colorectal cancer invasion depth using a deep learning model with multimodal data (with video).

BACKGROUND AND AIMS: The optical diagnosis of colorectal cancer (CRC) invasion depth with white ligh...

Not So Smart? Artificial Intelligence May Need to Go Deeper to Predict Colorectal Cancer Invasion Depth.

The incidence of cardiovascular thrombotic complications after laparoscopic resection in colorectal cancer in Japanese hospitals: A large-scale clinical study.

AIM: The aim of this retrospective study was to investigate the incidence of cardiovascular thrombot...

Artificial intelligence for the assessment of bowel preparation.

BACKGROUND AND AIMS: A reliable assessment of bowel preparation is important to ensure high-quality ...

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations.

A growing amount of evidence suggests that long non-coding RNAs (lncRNAs) play important roles in th...

Deep reconstruction-recoding network for unsupervised domain adaptation and multi-center generalization in colonoscopy polyp detection.

BACKGROUND AND OBJECTIVE: Currently, the best performing methods in colonoscopy polyp detection are ...

ALA-Net: Adaptive Lesion-Aware Attention Network for 3D Colorectal Tumor Segmentation.

Accurate and reliable segmentation of colorectal tumors and surrounding colorectal tissues on 3D mag...

Deep neural network for video colonoscopy of ulcerative colitis: a cross-sectional study.

BACKGROUND: A combination of endoscopic and histological evaluation is important in the management o...

A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy.

Colorectal cancer (CRC) is the third most detected cancer and the second foremost cause of cancer de...

Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor.

BACKGROUND: Rapid intraoperative diagnosis for unconfirmed pulmonary tumor is extremely important fo...

Cuprous oxide coated silver/graphitic carbon nitride/cadmium sulfide nanocomposite heterostructure: Specific recognition of carcinoembryonic antigen through sandwich-type mechanism.

The development of the effective diagnostic method for the determination of cancer biomarkers is one...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric c...

Deep Learning-Based Diagnosis Method of Emergency Colorectal Pathology.

One of the most common malignant tumors of the digestive tract is emergency colorectal cancer. In re...

Using Machine Learning Approaches to Predict Short-Term Risk of Cardiotoxicity Among Patients with Colorectal Cancer After Starting Fluoropyrimidine-Based Chemotherapy.

Cardiotoxicity is a severe side effect for colorectal cancer (CRC) patients undergoing fluoropyrimid...

Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain.

Automatic pattern recognition using deep learning techniques has become increasingly important. Unfo...

Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging.

In current clinical practice, tumor response assessment is usually based on tumor size change on ser...

A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinoma.

OBJECTIVE: To develop and validate a deep learning nomogram (DLN) model constructed from non-contras...

Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans.

Deep learning (DL) is a breakthrough technology for medical imaging with high sample size requiremen...

Machine learning random forest for predicting oncosomatic variant NGS analysis.

Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analy...

Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

PURPOSE: This study aimed to explore the predictive ability of deep learning (DL) for the common epi...