id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_xy6hzbddgretvirrb2rknk2beu	Joan Vila-Francés	Expert system for predicting unstable angina based on Bayesian networks	2013	7	.pdf	application/pdf	4524	431	66	The validation results, with a negative predictive value (NPV) of 91%, demonstrate its applicability to help clinicians. The final model was implemented as a web application that is currently been validated by clinician a Bayesian Network model trained with a dataset of 1164 cases. Most of the input variables are binary, and hence they are converted to discrete nodes of the Bayesian Network directly. This tool evaluates the risk of heart attack on incoming patients with chest pain in cases, a probabilistic inference motor based on a Bayesian Network in the form with the evidences from the incoming patient (symptoms and clinical history); then the application processes the data The tool uses a Bayesian Network to evaluate the risk of suffering a heart attack. model uses a FAN network structure with discrete nodes. Expert system for predicting unstable angina based on Bayesian networks Expert system for predicting unstable angina based on Bayesian networks	./cache/work_xy6hzbddgretvirrb2rknk2beu.pdf	./txt/work_xy6hzbddgretvirrb2rknk2beu.txt