Open AccessPrediction of ARDS Syndrome and CAD Using Multilayer Perceptron
Author(s) -
M. Mohanasundari,
S. Prasanth
Publication year - 2020
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/ijsrst207225
Subject(s) - ards , cad , coronary artery disease , medicine , feature selection , cardiology , pattern recognition (psychology) , computer science , artificial intelligence , lung , engineering , engineering drawing
Acute Respiratory Distress Syndrome (ARDS) and Coronary artery heart Disease (CAD) isa critical condition occurring in ill patients. Our proposed system is to predict ARDS and CAD in hospitalized patients using only physiological signals as heart rate and breathing rate. This based on hypothesis testing is developed to detect whether subjects signals deviate from their initial states. The approach is applied on mechanically ventilated subjects in the MIMIC II database. Hybrid method for CAD diagnosis, including risk factor identification using correlation based feature subset selection with particle swam optimization search method and K-Means clustering algorithms. This proposed system is increasing the efficiency and accuracy of predicting the ARDS and CAD diseases.