Lung Disease Detection Using Deep Learning Techniques


The purpose of this white paper is to articulate the impact of computer vision and machine learning, and how it has revolutionized the way medical professionals diagnose lung diseases with its performance through algorithms that can learn, adapt, and perform predictive data analysis.


Machine Learning and Deep Learning Techniques are the Future

There can be no denying that advanced technology has had a massive impact on the medical community. It has revolutionized the industry and provides solutions for treating previously irreversible and terminal diseases. The use of deep learning technology has been instrumental in examining different images and identifying diseases with unmatched results. It has allowed better disease monitoring, treatment planning, and early detection, which has firmly earned deep learning its place in medical science.

The NIH acquired scans of over 30,000 patients (mostly with advanced lung disease) and compiled their data. The patients were voluntarily enrolled in the clinical trials and were partners in research. The research clearly showed the positive benefits of deep learning techniques, because reading and diagnosing chest x-ray images isn’t easy. It requires knowledge of pathology, physiology, and anatomical principles, as well as careful observation. All of that can be handled by deep learning techniques, which deliver a consistent and accurate diagnosis.

Apart from that, deep learning techniques also offer the following:

  • Help identify slow changes occurring over the course of multiple chest x-rays
  • Create a virtual radiology resident that can later be taught to read more complex images like CT and MRI in the future.
  • Benefit patients in developing countries that don’t have access to radiologists

Not only can deep learning and machine learning techniques help inexperienced radiologists but can also benefit the healthcare sector by reducing the amount of redundant additional tests that are taken before confirming the diagnosis.


There is no denying the potential and accuracy of deep learning when it comes to examining hundreds of complex images while identifying and diagnosing different diseases. It offers excellent insight into the early detection of lung disease, and the best part is that the technology can be easily integrated into existing health systems for creating integrated solutions based on data.