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

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.

Authors

Institutions

Publication Details

Journal
South Eastern European Journal of Public Health
Published
2024-09-02
DOI
https://doi.org/10.70135/seejph.vi.803
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Anupa Sinha, Yalakala Dinesh Kumar
South Eastern European Journal of Public Health
COVID-19 diagnosis using AI
article

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

Anupa Sinha, Yalakala Dinesh Kumar
article en

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.

South Eastern European Journal of Public Health
Kalinga University (IN)
Good health and well-being
Openalex Percentile: Top 74%
COVID-19 diagnosis using AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.