Colon Cancer

Identification of clinical trait-related small RNA biomarkers with weighted gene co-expression network analysis for personalized medicine in endocervical adenocarcinoma.

Endocervical adenocarcinoma (EAC) is an aggressive type of endocervical cancer. At present, molecula...

Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study.

Histopathological growth patterns (HGPs) are independent prognosticators for colorectal liver metast...

Deep learning for automated bowel preparation assessment during colonoscopy: time to embrace a new approach?

Multi-step validation of a deep learning-based system for the quantification of bowel preparation: a prospective, observational study.

BACKGROUND: Inadequate bowel preparation is associated with a decrease in adenoma detection rate (AD...

functional cell phenotyping reveals microdomain networks in colorectal cancer recurrence.

Tumors are dynamic ecosystems comprising localized niches (microdomains), possessing distinct compos...

Personalised Medicine for Colorectal Cancer Using Mechanism-Based Machine Learning Models.

Gaining insight into the mechanisms of signal transduction networks (STNs) by using critical feature...

Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial).

BACKGROUND & AIMS: Artificial intelligence-based computer-aided polyp detection (CADe) systems are i...

Highly accurate diagnosis of lung adenocarcinoma and squamous cell carcinoma tissues by deep learning.

Intraoperative detection of the marginal tissues is the last and most important step to complete the...

Weakly supervised learning on unannotated H&E-stained slides predicts BRAF mutation in thyroid cancer with high accuracy.

Deep neural networks (DNNs) that predict mutational status from H&E slides of cancers can enable ine...

Kefir modulates gut microbiota and reduces DMH-associated colorectal cancer via regulation of intestinal inflammation in adulthood offsprings programmed by neonatal overfeeding.

Obesity is associated with chronic inflammation, intestinal dysbiosis, and colorectal cancer risk. T...

Selection, Visualization, and Interpretation of Deep Features in Lung Adenocarcinoma and Squamous Cell Carcinoma.

Although deep learning networks applied to digital images have shown impressive results for many pat...

Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning.

Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of ...

Artificial intelligence-assisted colonoscopy: A prospective, multicenter, randomized controlled trial of polyp detection.

BACKGROUND: Artificial intelligence (AI) assistance has been considered as a promising way to improv...

Defining the next steps for artificial intelligence in colonoscopy.

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncoge...

Evaluation of novel LCI CAD EYE system for real time detection of colon polyps.

BACKGROUND: Linked color imaging (LCI) has been shown to be effective in multiple randomized control...

Automatic Polyp Segmentation in Colonoscopy Images Using a Modified Deep Convolutional Encoder-Decoder Architecture.

Colorectal cancer has become the third most commonly diagnosed form of cancer, and has the second hi...

Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.

Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment...

Artificial intelligence and polyp detection in colonoscopy: Use of a single neural network to achieve rapid polyp localization for clinical use.

BACKGROUND AND AIM: Artificial intelligence has been extensively studied to assist clinicians in pol...

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung canc...

The learning curve in robotic colorectal surgery compared with laparoscopic colorectal surgery: a systematic review.

AIM: The learning curve has implications for efficient surgical training. Robotic surgery is perceiv...