Analysis of ICU data of pediatric heart patients

Abstract

One of the most fatal conditions for pediatric disease is congenital heart disease (CHD). Reviewing massive databases, comparing them, and mining them for information that can be used to identify, monitor, and treat illnesses like CHD is the key to treating cardiovascular disease. Cardiovascular disease can be predicted, prevented, managed, and treated with great effectiveness using big data analytics, which is well-known all over the world for its useful application in controlling, contrasting, and managing massive datasets. This study analyzes the post-operative ICU data. We analyzed the patient conditions of the ICU patients by using descriptive statistics. Here, we have selected the ICU parameters between different demographic groups by using chi-square test, t test and p value. Besides, this we also used different machine learning method to predict the patient condition. The outcomes will serve as a reference for medical professionals employing big data technology to predict and manage CHD patients in ICU.