Decision Support System Based on Deep Learning with Big Data for Pneumonia Prediction

Abstract

A bacterial, viral, or fungal infection of the lungs causes pneumonia in humans. It is the primary cause of global decline. Around 27% of deaths worldwide are attributable to this illness. A World Health Organisation report states that this serious infectious disease claims the lives of almost 2.5 million people annually. Early detection of chest illness, including pneumonia, can reduce the likelihood that the condition will worsen by allowing for the proper course of treatment. Accurate CT scans and CXR (chest X-ray) reports are renowned for being exact methods of diagnosis and prediction. This approach is trustworthy and non-invasive, and it can be used as a screening tool when a disease diagnosis is necessary. Nevertheless, research has demonstrated that even highly trained radiologists regularly fail to correctly identify pneumonia disease in its early stages. The severity of the sickness and the death rate increase as a result of diagnostic delays. Machine learning has affected every aspect of human life in the twenty-first century. It has a significant effect on the medical field in terms of early diagnosis of serious illnesses. Therefore, an intelligent health care system based on artificial intelligence (AI) was presented in this work for the early and accurate diagnosis of pneumonia disease.