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  • Open Access

    ARTICLE

    Modeling the Dynamics of Tuberculosis with Vaccination, Treatment, and Environmental Impact: Fractional Order Modeling

    Muhammad Altaf Khan1,*, Mahmoud H. DarAssi2, Irfan Ahmad3, Noha Mohammad Seyam4, Ebraheem Alzahrani5

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1365-1394, 2024, DOI:10.32604/cmes.2024.053681 - 27 September 2024

    Abstract A mathematical model is designed to investigate Tuberculosis (TB) disease under the vaccination, treatment, and environmental impact with real cases. First, we introduce the model formulation in non-integer order derivative and then, extend the model into fractional order derivative. The fractional system’s existence, uniqueness, and other relevant properties are shown. Then, we study the stability analysis of the equilibrium points. The disease-free equilibrium (DFE) is locally asymptotically stable (LAS) when . Further, we show the global asymptotical stability (GAS) of the endemic equilibrium (EE) for and for . The existence of bifurcation analysis in the More >

  • Open Access

    ARTICLE

    Tuberculosis Diagnosis and Visualization with a Large Vietnamese X-Ray Image Dataset

    Nguyen Trong Vinh1, Lam Thanh Hien1, Ha Manh Toan2, Ngo Duc Vinh3, Do Nang Toan2,*

    Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 281-299, 2024, DOI:10.32604/iasc.2024.045297 - 21 May 2024

    Abstract Tuberculosis is a dangerous disease to human life, and we need a lot of attempts to stop and reverse it. Significantly, in the COVID-19 pandemic, access to medical services for tuberculosis has become very difficult. The late detection of tuberculosis could lead to danger to patient health, even death. Vietnam is one of the countries heavily affected by the COVID-19 pandemic, and many residential areas as well as hospitals have to be isolated for a long time. Reality demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessing medical services,… More >

  • Open Access

    ARTICLE

    Identification of Tuberculosis and Coronavirus Patients Using Hybrid Deep Learning Models

    Mohammed A. Al Ghamdi*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 881-894, 2023, DOI:10.32604/cmc.2023.037826 - 08 June 2023

    Abstract Considerable resources, technology, and efforts are being utilized worldwide to eradicate the coronavirus. Although certain measures taken to prevent the further spread of the disease have been successful, efforts to completely wipe out the coronavirus have been insufficient. Coronavirus patients have symptoms similar to those of chest Tuberculosis (TB) or pneumonia patients. Chest tuberculosis and coronavirus are similar because both diseases affect the lungs, cause coughing and produce an irregular respiratory system. Both diseases can be confirmed through X-ray imaging. It is a difficult task to diagnose COVID-19, as coronavirus testing kits are neither excessively… More >

  • Open Access

    ARTICLE

    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 - 09 February 2023

    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… More >

  • Open Access

    ARTICLE

    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 - 28 December 2022

    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… More >

  • Open Access

    ARTICLE

    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 - 31 October 2022

    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… More >

  • Open Access

    ARTICLE

    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 - 01 June 2022

    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… More >

  • Open Access

    ARTICLE

    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 - 14 March 2022

    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 More >

  • Open Access

    ARTICLE

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

    XINJUN YANG1, AFTAB ALAM2, NAIYAR IQBAL3, KHALID RAZA4,*

    BIOCELL, Vol.45, No.6, pp. 1569-1583, 2021, DOI:10.32604/biocell.2021.017019 - 01 September 2021

    Abstract

    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

    More >

  • Open Access

    REVIEW

    Progresses of mycobacteriophage-based Mycobacterium tuberculosis detection

    ZICHEN LIU1,#, SIYAO GUO2,3,#, MENGZHI JI1, KAILI SUN1, ZHONGFANG LI4,*, XIANGYU FAN1,*

    BIOCELL, Vol.44, No.4, pp. 683-694, 2020, DOI:10.32604/biocell.2020.011713 - 24 December 2020

    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 More >

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