Pneumonia Diagnosis and Analysis System with Machine Learning

Pneumonia Diagnosis and Analysis System with Machine Learning

Shrunkhala S. Wankhede1, Mahima P. Adhale2, Sejal T. Hiwase2, Sayali D. Khedikar2,

Tanushree S. Vaitage2

1Assistant Professor, Department of CSE, Priyadarshini Bhagwati College of Engineering, Nagpur

2Students, Department of CSE, Priyadarshini Bhagwati College of Engineering, Nagpur

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ABSTRACT: 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

Key Word: lung disease, machine learning, convolutional neural network, recurrent neural network, support vector machine, medical imaging, symptom assessment, Diagnostic test.