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  • Open Access


    Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm, Transfer Learning, and Model Compression

    Hassen Louati1,2, Ali Louati3,*, Elham Kariri3, Slim Bechikh2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2519-2547, 2024, DOI:10.32604/cmes.2023.030806

    Abstract Recent developments in Computer Vision have presented novel opportunities to tackle complex healthcare issues, particularly in the field of lung disease diagnosis. One promising avenue involves the use of chest X-Rays, which are commonly utilized in radiology. To fully exploit their potential, researchers have suggested utilizing deep learning methods to construct computer-aided diagnostic systems. However, constructing and compressing these systems presents a significant challenge, as it relies heavily on the expertise of data scientists. To tackle this issue, we propose an automated approach that utilizes an evolutionary algorithm (EA) to optimize the design and compression More >

  • Open Access


    Molecular mechanisms and cellular process in signal transduction pathway related to air pollutants in obstructive lung diseases: A mini-review


    BIOCELL, Vol.47, No.8, pp. 1703-1708, 2023, DOI:10.32604/biocell.2023.028975

    Abstract Exposure to air pollutants such as PM10, PM2.5, PM0.1, O3, CO, NO2, and SO2, and biological pollutants are important factors causing the evolution and furtherance of obstructive lung diseases (OLD), including asthma and chronic obstructive pulmonary disease (COPD). Asthma is the most frequent chronic inflammatory airway disease, characterized by breathlessness, wheezing, chest tightness, and cough, together with the presence of exaggerated expiratory airflow fluctuation that varies over time. COPD is a heterogeneous lung condition characterized by chronic respiratory symptoms such as dyspnea, cough, expectoration, and/or exacerbations due to abnormalities of the airways and/or alveoli that cause persistent, often… More >

  • Open Access


    Advance IoT Intelligent Healthcare System for Lung Disease Classification Using Ensemble Techniques

    J. Prabakaran1,*, P. Selvaraj2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2141-2157, 2023, DOI:10.32604/csse.2023.034210

    Abstract In healthcare systems, the Internet of Things (IoT) innovation and development approached new ways to evaluate patient data. A cloud-based platform tends to process data generated by IoT medical devices instead of high storage, and computational hardware. In this paper, an intelligent healthcare system has been proposed for the prediction and severity analysis of lung disease from chest computer tomography (CT) images of patients with pneumonia, Covid-19, tuberculosis (TB), and cancer. Firstly, the CT images are captured and transmitted to the fog node through IoT devices. In the fog node, the image gets modified into… More >

  • Open Access


    STAT3 Polymorphism Associates With mTOR Inhibitor-Induced Interstitial Lung Disease in Patients With Renal Cell Carcinoma

    Kazuhiro Yamamoto*, Takeshi Ioroi*, Kazuaki Shinomiya, Ayaka Yoshida*, Kenichi Harada, Masato Fujisawa, Tomohiro Omura*, Yasuaki Ikemi§, Shunsaku Nakagawa§, Atsushi Yonezawa§, Osamu Ogawa, Kazuo Matsubara§, Takuya Iwamoto#, Kohei Nishikawa**, Sayaka Hayashi††, Daichi Tohara††, Yoji Murakami‡‡, Takanobu Motoshima‡‡, Hirofumi Jono††, Ikuko Yano

    Oncology Research, Vol.29, No.1, pp. 11-23, 2021, DOI:10.3727/096504022X16418911579334

    Abstract We evaluated the association of signal transducer and activator of transcription 3 (STAT3) polymorphisms with the incidence of mammalian target of rapamycin (mTOR) inhibitor-induced interstitial lung disease (ILD) in patients with renal cell carcinoma (RCC). We also used lung-derived cell lines to investigate the mechanisms of this association. Japanese patients with metastatic RCC who were treated with mTOR inhibitors were genotyped for the STAT3 polymorphism, rs4796793 (−1697C/G). We evaluated the association of the STAT3 genotype with the incidence of ILD and therapeutic outcome. In the 57 patients included in the primary analysis, the ILD rate… More >

  • Open Access


    Practical Machine Learning Techniques for COVID-19 Detection Using Chest X-Ray Images

    Yurananatul Mangalmurti, Naruemon Wattanapongsakorn*

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 733-752, 2022, DOI:10.32604/iasc.2022.025073

    Abstract This paper presents effective techniques for automatic detection/classification of COVID-19 and other lung diseases using machine learning, including deep learning with convolutional neural networks (CNN) and classical machine learning techniques. We had access to a large number of chest X-ray images to use as input data. The data contains various categories including COVID-19, Pneumonia, Pneumothorax, Atelectasis, and Normal (without disease). In addition, chest X-ray images with many findings (abnormalities and diseases) from the National Institutes of Health (NIH) was also considered. Our deep learning approach used a CNN architecture with VGG16 and VGG19 models which… More >

  • Open Access


    Non-Invasive Early Diagnosis of Obstructive Lung Diseases Leveraging Machine Learning Algorithms

    Mujeeb Ur Rehman1,*, Maha Driss2,3, Abdukodir Khakimov4, Sohail Khalid1

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5681-5697, 2022, DOI:10.32604/cmc.2022.025840

    Abstract Lungs are a vital human body organ, and different Obstructive Lung Diseases (OLD) such as asthma, bronchitis, or lung cancer are caused by shortcomings within the lungs. Therefore, early diagnosis of OLD is crucial for such patients suffering from OLD since, after early diagnosis, breathing exercises and medical precautions can effectively improve their health state. A secure non-invasive early diagnosis of OLD is a primordial need, and in this context, digital image processing supported by Artificial Intelligence (AI) techniques is reliable and widely used in the medical field, especially for improving early disease diagnosis. Hence,… More >

  • Open Access


    Forced vital capacity predicts morbidity and mortality in adults with repaired tetralogy of Fallot

    Katie E. Cohen1, Matthew W. Buelow1, Jennifer Dixon1, Ruta Brazauskas2, Scott B. Cohen3, Michael G. Earing1,3, Salil Ginde1

    Congenital Heart Disease, Vol.12, No.4, pp. 435-440, 2017, DOI:10.1111/chd.12470

    Abstract Objective: Abnormal lung function characterized by a reduced forced vital capacity (FVC) is common in adults with repaired tetralogy of Fallot (TOF) and is associated with previous thoracotomies and sternotomies. The impact of abnormal lung function on clinical outcomes in adult patients with repaired TOF is unclear. The aim of this study was to determine the impact of abnormal lung function on the outcome of hospitalization and death in adults with repaired TOF when analyzed with other traditional cardiac risk factors.
    Design: Retrospective study of adults with repaired TOF, who underwent spirometry between 2000 and 2014. FVC… More >

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