Lung Disease Detection From Chest X-ray Images Using Hybrid Machine Learning Model

Abstract

Lots of people die due to lung diseases in India alone.
The human lungs is a complicated system where different disease
occur at different parts of this system. Some diseases, such as
asthma, affect the airways of the lungs causing inflammation
which results in shortness of breath. Diseases such as pneumonia,
tuberculosis, and lung cancer affect the air sacs inside the lungs,
which are called alveoli. The Covid-19 corona virus has
significantly disrupted the global economy, culture, and health
systems. Since the corona virus usually first causes symptoms
in the lungs of patients, chest X-ray images can be useful in
accurately diagnosing a patient.The rapid advancement in deep
learning techniques has significantly impacted the field of medical
imaging, particularly in diagnosing lung diseases. The proposed
system aims to develop a hybrid machine learning model using
InceptionV3 and DenseNet for the detection of lung diseases from
chest X-ray images. Our work highlights the potential of machine
learning models in automating the detection of lung diseases,
providing insights into their comparative strengths and suggesting
new pathways for future research