Abstract

Environmental changes, pollution, and different harmful daily habits—such as smoking and drinking—are major contributors to the number of lung diseases that need early diagnosis. Smoking not only distresses smokers but also those around them, frequently leading to respirational issues. This study presents a hybrid model that analyses patient symptoms to categorize the presence of lung diseases and dispenses a severity mark demonstrating whether the state is mild, moderate, or severe. If the user has an X-ray image and wants additional verification, they can upload the image to receive diagnostic results. The primary aim is to detect chronic lung diseases at an early stage, increasing the likelihood of timely treatment and improved survival rates. The proposed assumption includes hybrid machine learning techniques to predict conditions such as Tuberculosis, Pneumonia, and COPD [1,2,6]. Using Hybrid machine learning algorithm98.1 percent accuracy has been achieved.

References

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