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  • Open Access

    ARTICLE

    Identification of Thoracic Diseases by Exploiting Deep Neural Networks

    Saleh Albahli1, Hafiz Tayyab Rauf2,*, Muhammad Arif3, Md Tabrez Nafis4, Abdulelah Algosaibi5

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3139-3149, 2021, DOI:10.32604/cmc.2021.014134

    Abstract With the increasing demand for doctors in chest related diseases, there is a 15% performance gap every five years. If this gap is not filled with effective chest disease detection automation, the healthcare industry may face unfavorable consequences. There are only several studies that targeted X-ray images of cardiothoracic diseases. Most of the studies only targeted a single disease, which is inadequate. Although some related studies have provided an identification framework for all classes, the results are not encouraging due to a lack of data and imbalanced data issues. This research provides a significant contribution to Generative Adversarial Network (GAN)… More >

  • Open Access

    ARTICLE

    Recognition and Classification of Pomegranate Leaves Diseases by Image Processing and Machine Learning Techniques

    Mangena Venu Madhavan1, Dang Ngoc Hoang Thanh2, Aditya Khamparia1,*, Sagar Pande1, Rahul Malik1, Deepak Gupta3

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2939-2955, 2021, DOI:10.32604/cmc.2021.012466

    Abstract Disease recognition in plants is one of the essential problems in agricultural image processing. This article focuses on designing a framework that can recognize and classify diseases on pomegranate plants exactly. The framework utilizes image processing techniques such as image acquisition, image resizing, image enhancement, image segmentation, ROI extraction (region of interest), and feature extraction. An image dataset related to pomegranate leaf disease is utilized to implement the framework, divided into a training set and a test set. In the implementation process, techniques such as image enhancement and image segmentation are primarily used for identifying ROI and features. An image… More >

  • Open Access

    ARTICLE

    Between Chronic Diseases and Geriatric Depression: Mediational Effects of Activities of Daily Living (ADLs) Disability Among Older Adults

    Yi Yang1,2,* , Tao Li3

    International Journal of Mental Health Promotion, Vol.22, No.4, pp. 249-259, 2020, DOI:10.32604/IJMHP.2020.014321

    Abstract This study is aimed to explore relations between chronic diseases, activities of daily living (ADLs) disability and depression among older adults, particularly ADLs disability mediational effects on the correlation between chronic diseases and geriatric depression. Records of 5931 participants at age 60 and above from China Health and Retirement Longitudinal Study (CHARLS) in 2015 were used as valid samples for data relating to their chronic diseases index, ADLs scale and Center for Epidemiologic Studies Depression (CES-D) scale. Our findings confirm that among older adults, 75.9% are afflicted with chronic diseases and 52.5% have ADLs difficulty or disability, and that there… More >

  • Open Access

    ARTICLE

    Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM Approaches

    Jalal Sadoon Hameed Al-bayati1,*, Burak Berk Üstündağ2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1479-1496, 2021, DOI:10.32604/cmc.2020.013329

    Abstract The Fused Modified Grasshopper Optimization Algorithm has been proposed, which selects the most specific feature sets from images of the disease of plant leaves. The Proposed algorithm ensures the detection of diseases during the early stages of the diagnosis of leaf disease by farmers and, finally, the crop needed to be controlled by farmers to ensure the survival and protection of plants. In this study, a novel approach has been suggested based on the standard optimization algorithm for grasshopper and the selection of features. Leaf conditions in plants are a major factor in reducing crop yield and quality. Any delay… More >

  • Open Access

    ARTICLE

    Deep Learning-Based Classification of Fruit Diseases: An Application for Precision Agriculture

    Inzamam Mashood Nasir1, Asima Bibi2, Jamal Hussain Shah2, Muhammad Attique Khan1, Muhammad Sharif2, Khalid Iqbal3, Yunyoung Nam4, Seifedine Kadry5,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1949-1962, 2021, DOI:10.32604/cmc.2020.012945

    Abstract Agriculture is essential for the economy and plant disease must be minimized. Early recognition of problems is important, but the manual inspection is slow, error-prone, and has high manpower and time requirements. Artificial intelligence can be used to extract fruit color, shape, or texture data, thus aiding the detection of infections. Recently, the convolutional neural network (CNN) techniques show a massive success for image classification tasks. CNN extracts more detailed features and can work efficiently with large datasets. In this work, we used a combined deep neural network and contour feature-based approach to classify fruits and their diseases. A fine-tuned,… More >

  • Open Access

    ARTICLE

    Smart CardioWatch System for Patients with Cardiovascular Diseases Who Live Alone

    Raisa Nazir Ahmed Kazi1,*, Manjur Kolhar2, Faiza Rizwan2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1237-1250, 2021, DOI:10.32604/cmc.2020.012707

    Abstract The widespread use of smartwatches has increased their specific and complementary activities in the health sector for patient’s prognosis. In this study, we propose a framework referred to as smart forecasting CardioWatch (SCW) to measure the heart-rate variation (HRV) for patients with myocardial infarction (MI) who live alone or are outside their homes. In this study, HRV is used as a vital alarming sign for patients with MI. The performance of the proposed framework is measured using machine learning and deep learning techniques, namely, support vector machine, logistic regression, and decision-tree classification techniques. The results indicated that the analysis of… More >

  • Open Access

    ARTICLE

    Severity Recognition of Aloe vera Diseases Using AI in Tensor Flow Domain

    Nazeer Muhammad1, Rubab2, Nargis Bibi3, Oh-Young Song4, Muhammad Attique Khan5,*, Sajid Ali Khan6

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2199-2216, 2021, DOI:10.32604/cmc.2020.012257

    Abstract Agriculture plays an important role in the economy of all countries. However, plant diseases may badly affect the quality of food, production, and ultimately the economy. For plant disease detection and management, agriculturalists spend a huge amount of money. However, the manual detection method of plant diseases is complicated and time-consuming. Consequently, automated systems for plant disease detection using machine learning (ML) approaches are proposed. However, most of the existing ML techniques of plants diseases recognition are based on handcrafted features and they rarely deal with huge amount of input data. To address the issue, this article proposes a fully… More >

  • Open Access

    REVIEW

    Biological and Functional Properties of Wedelolactone in Human Chronic Diseases

    Ramachandran Vinyagam1, Pradeep Kumar2, Kyung Eun Lee1,3, Baojun Xu4, Muhammad Nurul Matin5,*, Sang Gu Kang1,3,*

    Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 1-15, 2021, DOI:10.32604/phyton.2020.013388

    Abstract Medicinal herbs are well known and studied over the past millennia in most of the developing countries as a rational means of treatment against various diseases and disorders. Wedelolactone (WDL), a major bioactive compound in Eclipta prostrata L (Eclipta alba L), has been reported with potential benefits in human health against chronic diseases. However, a comprehensive study on WDL pharmacological benefits in various ailments, to the best of our knowledge, is not yet reported. Thereof, the present review provides the recent therapeutic applications in reference to biological and functional activities against major human chronic diseases, including cardiovascular, cancer, diabetes mellitus,… More >

  • Open Access

    ARTICLE

    Image Recognition of Citrus Diseases Based on Deep Learning

    Zongshuai Liu1, Xuyu Xiang1,2,*, Jiaohua Qin1, Yun Tan1, Qin Zhang1, Neal N. Xiong3

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 457-466, 2021, DOI:10.32604/cmc.2020.012165

    Abstract In recent years, with the development of machine learning and deep learning, it is possible to identify and even control crop diseases by using electronic devices instead of manual observation. In this paper, an image recognition method of citrus diseases based on deep learning is proposed. We built a citrus image dataset including six common citrus diseases. The deep learning network is used to train and learn these images, which can effectively identify and classify crop diseases. In the experiment, we use MobileNetV2 model as the primary network and compare it with other network models in the aspect of speed,… More >

  • Open Access

    ARTICLE

    The role of HBD-2, HBD-3, and calprotectin in the relationship between chronic periodontitis and atherosclerosis

    MEHMET TASPINAR1,2,*, ALIHAN BOZOGLAN3,4, ABDULLAH SECKIN ERTUGRUL5, LEVENT ELMAS6

    BIOCELL, Vol.44, No.3, pp. 337-344, 2020, DOI:10.32604/biocell.2020.011470

    Abstract This study was carried out to compare individuals diagnosed with atherosclerosis and periodontal periodontitis based on the degree of change in the human beta-defensins (HBD) HBD-2, HBD-3, and calprotectin. Atherosclerosis is the most frequently observed cardiovascular disease. Dental and periodontal infections are known to provide a considerable basis for atheroma plaque formation. The study group consists of a total number of 40 subjects, with 20 patients diagnosed with atherosclerosis and chronic periodontitis and 20 systemically healthy patients diagnosed with chronic periodontitis. Clinical periodontal and blood parameters and HBD-2, HBD-3, and calprotectin biomarkers in the gingival crevicular fluid were measured. In… More >

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