The Evolution of Machine Learning In TB Diagnostics: Unlocking Patterns and Insights

PSM News /

Sep 23,2023

 

At a staggering rate of 188 people per every 100,000, India has a lot to do. Thankfully, tuberculosis is both preventable and curable, especially if it is detected early enough and treated in good time. With emerging machine learning algorithms, TB diagnosis seems to have taken a new dimension with computer-aided diagnostics (CAD) measures now taking centre stage in many climes.

 

The severity of tuberculosis (TB) makes it a troubling crisis across the globe, especially as it is responsible for millions of deaths around the world. According to the World Health Organisation.

 

That same year, about 2.59 million cases were recorded in India by the WHO. At a staggering rate of 188 people per every 100,000, India has a lot to do. Thankfully, tuberculosis is both preventable and curable, especially if it is detected early enough and treated in good time. With emerging machine learning algorithms, TB diagnosis seems to have taken a new dimension with computer-aided diagnostics (CAD) measures now taking centre stage in many climes.

 

The rise of computer-aided diagnostics has certainly added impetus to the drive for better TB diagnosis, especially because of better medical imaging that gives radiologists more precise interpretation of the patient's chest, blood, spine, or brain, depending on the part of the body that is affected. One of such tools is the CAD model which offers precise diagnosis of the TB cavity and clearly displays areas of interest when observing the chest x-ray image. This is a huge improvement on preexisting CAD systems which could not identify TB cavities, as a result of the lung field's superimposed anatomic parts.

 

Tools like deep learning, a component of AI, is also quickly becoming a trend among top diagnostics and health centres that has brought about increased diagnostic precision. TB detection has also been enhanced with more recent systems that support techniques like masking, texture analysis, as well as chest radiograph analysis. Accurate TB diagnosis has evaded radiologists and other diagnostic experts for many years due to the complex nature of the disease and how it can present in different parts of the body, but modern AI tools are changing the story.

 

Source:The Economic Times