AIMC Topic: Colonic Neoplasms
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An Enhancement of Computer Aided Approach for Colon Cancer Detection in WCE Images Using ROI Based Color Histogram and SVM2.
Journal of medical systems
Jan 5, 2019
The colon cancer is formed by uncontrollable growth of abnormal cells in large intestine or colon that can affect both men and women and it is third cancer disease in the world. At present, Wireless Capsule Endoscopy (WCE) screening method is utilize...
Tuning model parameters in class-imbalanced learning with precision-recall curve.
Biometrical journal. Biometrische Zeitschrift
Dec 12, 2018
An issue for class-imbalanced learning is what assessment metric should be employed. So far, precision-recall curve (PRC) as a metric is rarely used in practice as compared with its alternative of receiver operating characteristic (ROC). This study i...
Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.
Nature biomedical engineering
Oct 10, 2018
The detection and removal of precancerous polyps via colonoscopy is the gold standard for the prevention of colon cancer. However, the detection rate of adenomatous polyps can vary significantly among endoscopists. Here, we show that a machine-learni...
Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.
Journal of clinical monitoring and computing
Sep 24, 2018
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting ado...
Humans
Artificial Intelligence
Infusions, Intravenous
Ketorolac
Data Interpretation, Statistical
Reproducibility of Results
Signal Processing, Computer-Assisted
Patient Compliance
Pilot Projects
Colonic Neoplasms
Monitoring, Intraoperative
Patient Readmission
Treatment Outcome
Machine Learning
Medical Informatics
Colorectal Surgery
Software
Algorithms
Inflammatory Bowel Diseases
Is Robotic Complete Mesocolic Excision Feasible for Transverse Colon Cancer?
Journal of laparoendoscopic & advanced surgical techniques. Part A
Jun 7, 2018
Laparoscopic complete mesocolic excision (CME) for transverse colon cancer is technically challenging. Robotic technology has been developed to reduce technical limitations of laparoscopy. Yet, no data are available on the role of robotic approach f...
Natural Language Processing Accurately Calculates Adenoma and Sessile Serrated Polyp Detection Rates.
Digestive diseases and sciences
Apr 26, 2018
BACKGROUND: ADR is a widely used colonoscopy quality indicator. Calculation of ADR is labor-intensive and cumbersome using current electronic medical databases. Natural language processing (NLP) is a method used to extract meaning from unstructured o...
Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience.
Gastroenterology
Apr 11, 2018
A Functional Signature Ontology (FUSION) screen detects an AMPK inhibitor with selective toxicity toward human colon tumor cells.
Scientific reports
Feb 28, 2018
AMPK is a serine threonine kinase composed of a heterotrimer of a catalytic, kinase-containing α and regulatory β and γ subunits. Here we show that individual AMPK subunit expression and requirement for survival varies across colon cancer cell lines....
Validation of an online risk calculator for the prediction of anastomotic leak after colon cancer surgery and preliminary exploration of artificial intelligence-based analytics.
Techniques in coloproctology
Oct 28, 2017
BACKGROUND: Recently published data support the use of a web-based risk calculator ( www.anastomoticleak.com ) for the prediction of anastomotic leak after colectomy. The aim of this study was to externally validate this calculator on a larger datase...
Survivability prediction of colon cancer patients using neural networks.
Health informatics journal
Sep 19, 2017
We utilize deep neural networks to develop prediction models for patient survival and conditional survival of colon cancer. Our models are trained and validated on data obtained from the Surveillance, Epidemiology, and End Results Program. We provide...
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