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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM37869
Volume:
8 |
10 |
Oct 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Pneumonia Diagnosis with Analysis System using Machine Learning”. Indicates that if the a Pneumonia is a major public health problem that causes a significant morbidity and mortality burden worldwide. Diagnosing pneumonia is often difficult and requires a combination of symptoms, physical examination, and ma ging studies. This research paper introduces the use of m machine learning to improve lung disease diagnosis and analysis, providing fast, accurate, and cost-effective solute for lung disease diagnosis. Recurrent Neural Network (RNN), and Support Vector Machines (SVM) to anal yet medical data, including images, test results, and clinical symptoms. The system is designed to integrate with existing medical systems to provide a better and more efficient experience for doctors and patients. Positive Predictive Value (PPV). The results show that the proposed s system outperforms human experts in terms of accuracy and efficiency, and reduces the time and cost of diagnosis Pneumonia is diagnosed and treated. By leveraging the power of machine learning algorithms, the system can provide doctors and patients with fast, accurate, and cost-effective solution the ultimately improve patient outcomes and reduce medical costs
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Publication Date
8/9/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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