Abstract
Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including tuberculosis. We built a deep convolutional neural network (CNN) model to assess the generalizability of the deep learning model using a publicly accessible tuberculosis dataset. This study was able to reliably detect tuberculosis (TB) from chest X-ray images by utilizing image preprocessing, data augmentation, and deep learning classification techniques. Four distinct deep CNNs (Xception, InceptionV3, InceptionResNetV2, and MobileNetV2) were trained, validated, and evaluated for the classification of tuberculosis and nontuberculosis cases using transfer learning from their pretrained starting weights. With an F1-score of 99 percent, InceptionResNetV2 had the highest accuracy. This research is more accurate than earlier published work. Additionally, it outperforms all other models in terms of reliability. The suggested approach, with its state-of-the-art performance, may be helpful for computer-assisted rapid TB detection.
Highlights
TB is the world’s second most lethal infectious disease, trailing only human immunodeficiency virus (HIV), with an estimated 1.4 million deaths in 2019 [1]
True positives (TP) are tuberculosis images that were correctly identified as such; true negatives (TN) are normal images that were correctly identified as such; false positives (FP) are normal images that were incorrectly identified as tuberculosis images; and false negatives (FN) are normal tuberculosis images
Due to a shortage of radiologists in resource-limited areas, technologyassisted tuberculosis diagnosis is required to help reduce the time and effort spent on tuberculosis detection
Summary
TB is the world’s second most lethal infectious disease, trailing only human immunodeficiency virus (HIV), with an estimated 1.4 million deaths in 2019 [1]. It is most often associated with the lungs, it may affect other organs such as the stomach (abdomen), glands, bones, and the neurological system. E top thirty tuberculosis-burdening countries accounted for 87% of tuberculosis cases in 2019 [2]. Ere are 5.6 million men, 3.2 million women, and 1.2 million children in the country. Tuberculosis may be cured if diagnosed early and treated appropriately [3]. Antibiotics are often given for a six-month period [4]
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