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  • Open Access


    Computer-Aided Diagnosis for Tuberculosis Classification with Water Strider Optimization Algorithm

    José Escorcia-Gutierrez1,*, Roosvel Soto-Diaz2, Natasha Madera3, Carlos Soto3, Francisco Burgos-Florez2, Alexander Rodríguez4, Romany F. Mansour5

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 1337-1353, 2023, DOI:10.32604/csse.2023.035253

    Abstract Computer-aided diagnosis (CAD) models exploit artificial intelligence (AI) for chest X-ray (CXR) examination to identify the presence of tuberculosis (TB) and can improve the feasibility and performance of CXR for TB screening and triage. At the same time, CXR interpretation is a time-consuming and subjective process. Furthermore, high resemblance among the radiological patterns of TB and other lung diseases can result in misdiagnosis. Therefore, computer-aided diagnosis (CAD) models using machine learning (ML) and deep learning (DL) can be designed for screening TB accurately. With this motivation, this article develops a Water Strider Optimization with Deep Transfer Learning Enabled Tuberculosis Classification… More >

  • Open Access


    Detecting Tuberculosis from Vietnamese X-Ray Imaging Using Transfer Learning Approach

    Ha Manh Toan1, Lam Thanh Hien2, Ngo Duc Vinh3, Do Nang Toan1,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5001-5016, 2023, DOI:10.32604/cmc.2023.033429

    Abstract Deep learning created a sharp rise in the development of autonomous image recognition systems, especially in the case of the medical field. Among lung problems, tuberculosis, caused by a bacterium called Mycobacterium tuberculosis, is a dangerous disease because of its infection and damage. When an infected person coughs or sneezes, tiny droplets can bring pathogens to others through inhaling. Tuberculosis mainly damages the lungs, but it also affects any part of the body. Moreover, during the period of the COVID-19 (coronavirus disease 2019) pandemic, the access to tuberculosis diagnosis and treatment has become more difficult, so early and simple detection… More >

  • Open Access


    A Hybrid Deep Fused Learning Approach to Segregate Infectious Diseases

    Jawad Rasheed1,*, Shtwai Alsubai2

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4239-4259, 2023, DOI:10.32604/cmc.2023.031969

    Abstract Humankind is facing another deadliest pandemic of all times in history, caused by COVID-19. Apart from this challenging pandemic, World Health Organization (WHO) considers tuberculosis (TB) as a preeminent infectious disease due to its high infection rate. Generally, both TB and COVID-19 severely affect the lungs, thus hardening the job of medical practitioners who can often misidentify these diseases in the current situation. Therefore, the time of need calls for an immediate and meticulous automatic diagnostic tool that can accurately discriminate both diseases. As one of the preliminary smart health systems that examine three clinical states (COVID-19, TB, and normal… More >

  • Open Access


    Histogram Matched Chest X-Rays Based Tuberculosis Detection Using CNN

    Joe Louis Paul Ignatius1,*, Sasirekha Selvakumar1, Kavin Gabriel Joe Louis Paul2, Aadhithya B. Kailash1, S. Keertivaas1, S. A. J. Akarvin Raja Prajan1

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 81-97, 2023, DOI:10.32604/csse.2023.025195

    Abstract Tuberculosis (TB) is a severe infection that mostly affects the lungs and kills millions of people’s lives every year. Tuberculosis can be diagnosed using chest X-rays (CXR) and data-driven deep learning (DL) approaches. Because of its better automated feature extraction capability, convolutional neural networks (CNNs) trained on natural images are particularly effective in image categorization. A combination of 3001 normal and 3001 TB CXR images was gathered for this study from different accessible public datasets. Ten different deep CNNs (Resnet50, Resnet101, Resnet152, InceptionV3, VGG16, VGG19, DenseNet121, DenseNet169, DenseNet201, MobileNet) are trained and tested for identifying TB and normal cases. This… More >

  • Open Access


    Modeling the Spread of Tuberculosis with Piecewise Differential Operators

    Abdon Atangana1,2, Ilknur Koca3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 787-814, 2022, DOI:10.32604/cmes.2022.019221

    Abstract Very recently, a new concept was introduced to capture crossover behaviors that exhibit changes in patterns. The aim was to model real-world problems exhibiting crossover from one process to another, for example, randomness to a power law. The concept was called piecewise calculus, as differential and integral operators are defined piece wisely. These behaviors have been observed in the spread of several infectious diseases, for example, tuberculosis. Therefore, in this paper, we aim at modeling the spread of tuberculosis using the concept of piecewise modeling. Several cases are considered, conditions under which the unique system solution is obtained are presented… More >

  • Open Access


    Repurposing of FDA-Approved drugs to predict new inhibitors against key regulatory genes in Mycobacterium tuberculosis


    BIOCELL, Vol.45, No.6, pp. 1569-1583, 2021, DOI:10.32604/biocell.2021.017019


    Tuberculosis (TB) disease has become one of the major public health concerns globally, especially in developing countries. Numerous research studies have already been carried out for TB, but we are still struggling for a complete and quick cure for it. The progress of Mycobacterium tuberculosis (MTB) strains resistant to existing drugs makes its cure and control very complicated. Therefore, it is the need of the hour to search for newer and effective drugs that can inhibit an increasing number of putative drug targets. We applied the drug repurposing concept to identify promising FDA-approved drugs against five key-regulatory genes (FurB, IdeR,… More >

  • Open Access


    Progresses of mycobacteriophage-based Mycobacterium tuberculosis detection


    BIOCELL, Vol.44, No.4, pp. 683-694, 2020, DOI:10.32604/biocell.2020.011713

    Abstract Tuberculosis (TB) remains a major cause of morbidity and mortality worldwide, particularly in developing countries. A rapid and efficient method for TB diagnosis is indispensable to check the trend of tuberculosis expansion. The emergence of drug-resistant bacteria has increased the challenge of rapid drug resistance tests. Due to its high specificity and sensitivity, bacteriophage-based diagnosis is intensively pursued. In this review, we mainly described mycobacteriophage-based diagnosis in TB detection, especially two prevalent approaches: fluorescent reporter phage and phage amplified biologically assay (PhaB). The rationale of reporter phage is that phage carrying fluorescent genes can infect host bacteria specifically. Phage amplified… More >

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