AIMC Topic: Colonic Neoplasms
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Application of machine-learning model to optimize colonic adenoma detection in India.
Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology
May 17, 2024
AIMS: There is limited data on the prevalence and risk factors of colonic adenoma from the Indian sub-continent. We aimed at developing a machine-learning model to optimize colonic adenoma detection in a prospective cohort.
Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.
Journal of gastroenterology and hepatology
May 9, 2024
BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its performance with traditional Cox regression.
Machine learning for predicting colon cancer recurrence.
Surgical oncology
Apr 19, 2024
INTRODUCTION: Colorectal cancer (CRC) is a global public health concern, ranking among the most commonly diagnosed malignancies worldwide. Despite advancements in treatment modalities, the specter of CRC recurrence remains a significant challenge, de...
Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology
Feb 5, 2024
PURPOSE: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer (CC). Oxaliplatin leads to lasting and disabling neurotoxicity. Reserving the regimen for patients ...
Impact of study design on adenoma detection in the evaluation of artificial intelligence-aided colonoscopy: a systematic review and meta-analysis.
Gastrointestinal endoscopy
Jan 24, 2024
BACKGROUND AND AIMS: Randomized controlled trials (RCTs) have reported that artificial intelligence (AI) improves endoscopic polyp detection. Different methodologies-namely, parallel and tandem designs-have been used to evaluate the efficacy of AI-as...
Linked-color imaging with or without artificial intelligence for adenoma detection: a randomized trial.
Endoscopy
Jan 8, 2024
BACKGROUND: Adenoma detection rate (ADR) is an important indicator of colonoscopy quality and colorectal cancer incidence. Both linked-color imaging (LCI) with artificial intelligence (LCA) and LCI alone increase adenoma detection during colonoscopy,...
Simple technique of double-layer enterotomy closure using a bidirectional barbed suture material when performing intracorporeal side-to-side anastomosis in robot-assisted right colectomy for colon cancer.
Techniques in coloproctology
Dec 11, 2023
Deep learning-based vessel automatic recognition for laparoscopic right hemicolectomy.
Surgical endoscopy
Nov 10, 2023
BACKGROUND: In laparoscopic right hemicolectomy (RHC) for right-sided colon cancer, accurate recognition of the vascular anatomy is required for appropriate lymph node harvesting and safe operative procedures. We aimed to develop a deep learning mode...
A hybrid machine learning feature selection model-HMLFSM to enhance gene classification applied to multiple colon cancers dataset.
PloS one
Nov 2, 2023
Colon cancer is a significant global health problem, and early detection is critical for improving survival rates. Traditional detection methods, such as colonoscopies, can be invasive and uncomfortable for patients. Machine Learning (ML) algorithms ...
A novel deep learning-based algorithm combining histopathological features with tissue areas to predict colorectal cancer survival from whole-slide images.
Journal of translational medicine
Oct 17, 2023
BACKGROUND: Many methodologies for selecting histopathological images, such as sample image patches or segment histology from regions of interest (ROIs) or whole-slide images (WSIs), have been utilized to develop survival models. With gigapixel WSIs ...
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