Predicting heart failure using deep neural network
Tuan Minh Le, Minh Thanh Vo, Linh Mai, Son Vu Truong Dao
Abstract
In the current health system, the diagnosis of heart failure is a difficult task and plays an important role in the early and effective treatment of patients. It is also based on the available diagnose data, from which a medical professional can make the best diagnosis for a patient. This process is very complicated, so with the development of machine learning, medical professionals will be supported to be able to make predictions of early heart failure with high accuracy. In this research, we want to predict heart failure using multilayer perceptron neural network (MLP). The prediction of heart failure dataset with the highest accuracy of 88% is better than the other research.
Topics & Concepts
Heart failureArtificial neural networkComputer scienceArtificial intelligenceTask (project management)Process (computing)Machine learningMultilayer perceptronMedical diagnosisMedical treatmentIntensive care medicineEngineeringMedicineCardiologySystems engineeringPathologyOperating systemArtificial Intelligence in HealthcareECG Monitoring and AnalysisCOVID-19 diagnosis using AI