Pneumonia Detection and Chest X-Rays: Comprehensive Analysis of Artificial Intelligence Techniques in Clinical and Radiological Insights

Abstract

Pneumonia continues to pose a considerable worldwide health burden, contributing significantly to morbidity and death across all age categories. The goal of this thorough Analysis study is to provide a thorough analysis of pneumonia, including information on its Pathophysiology, diagnostics, epidemiology, and treatment techniques. We'll investigate epidemiological elements using machine learning and deep learning such as incidence, prevalence, and risk factors to learn more about the disease's using artificial intelligence regional and demographic differences. The intricate Pathophysiology of pneumonia will be covered in detail, along with how host variables, environmental factors, and microbial agents interact. The merits and limits of various diagnostic procedures, such as sophisticated imaging, laboratory techniques, and clinical evaluation, will be analyzed critically. In addition, the discussion will go over current protocols and recommendations for treating pneumonia, stressing the need of supportive care, antibiotic treatment, and preventative measures. In order to provide physicians, researchers, and policymakers a thorough grasp of this common respiratory ailment, the article will discuss recent trends, difficulties, and future prospects in pneumonia research and clinical practice in using machine learning and deep learning.

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Identifiers

DOI

10.1109/ICoICI62503.2024.10696161

Journal

2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI)

Year

2024