A machine learning approach on chest X-rays for pediatric pneumonia detection.

ABSTRACT:

Background

According to the World Health Organization (WHO), pneumonia is the leading infectious cause of death in children below 5 years old. Hence, the early detection of pediatric pneumonia is crucial to reduce its morbidity and mortality rates. Even though chest radiography is the most commonly employed modality for pneumonia detection, recent studies highlight the existence of poor interobserver agreement in the chest X-ray interpretation of healthcare practitioners when it comes to diagnosing pediatric pneumonia. Thus, there is a significant need for automating the detection process to minimize the potential human error. Since Artificial Intelligence tools such as Deep Learning (DL) and Machine Learning (ML) have the potential to automate disease detection, many researchers e

SUBMITTER: Barakat N 

PROVIDER: S-EPMC10259147 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature