Designing Intelligent Software Systems for Early Detection of Chronic Mycobacterial Lung Disease
DOI:
https://doi.org/10.21015/vtse.v14i2.2321Abstract
Early detection of mycobacterial lung disease is tough because we have a lot of different clinical data and old diagnostic methods are not very good. This paper is about a healthcare software system that was made using a careful and organized approach. The chronic mycobacterial lung disease software system puts together data collection getting the data ready and analysis that uses intelligence. The chronic mycobacterial lung disease software system looks at chest X-ray pictures and clinical information using a kind of neural network. We tried it out with 5,200 examples and it was very good. It got the answer 95.1 percent of the time it was precise 94.6 percent of the time it caught most of the cases 95.8 percent of the time it had a good balance of precision and recall with a score of 95.2 percent and it was very good at telling the difference between things with a score of 0.97. When we compared it to models it did better every time. The results show that we need to use kinds of data and plan the software carefully to make chronic mycobacterial lung disease software systems that are reliable and easy to use. The chronic mycobacterial lung disease software system is very important, for mycobacterial lung disease diagnosis and treatment.
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