Jawad Rasheed^1,*, 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 >

Lin Yuan¹, Jingcheng Zhang^2,*, Quan Deng², Yingying Dong³, Haolin Wang², Xiankun Du²

Phyton-International Journal of Experimental Botany, Vol.92, No.2, pp. 611-628, 2023, DOI:10.32604/phyton.2022.023662 - 12 October 2022

Abstract Hyperspectral imaging technique is known as a promising non-destructive way for detecting plants diseases and pests. In most previous studies, the utilization of the whole spectrum or a large number of bands as well as the complexity of model structure severely hampers the application of the technique in practice. If a detection system can be established with a few bands and a relatively simple logic, it would be of great significance for application. This study established a method for identifying and discriminating three commonly occurring diseases and pests of wheat, i.e., powdery mildew, yellow rust… More >

Manjur Kolhar^*, Mohammed Misfer

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 529-542, 2023, DOI:10.32604/iasc.2023.030098 - 29 September 2022

Abstract Machine learning (ML) and cloud computing have now evolved to the point where they are able to be used effectively. Further improvement, however, is required when both of these technologies are combined to reap maximum benefits. A way of improving the system is by enabling healthcare workers to select appropriate machine learning algorithms for prediction and, secondly, by preserving the privacy of patient data so that it cannot be misused. The purpose of this paper is to combine these promising technologies to maintain the privacy of patient data during the disease prediction process. Treatment of… More >

FARIHA NUSRAT¹, MOHAMMAD TARIQUR RAHMAN², MUHAMMAD MANJURUL KARIM^3,*

BIOCELL, Vol.47, No.1, pp. 81-89, 2023, DOI:10.32604/biocell.2023.024635 - 26 September 2022

Abstract Bacterial endotoxins are a major concern in periodontal health and diseases owing to their structure and biological activity. With up-to-date knowledge of endotoxins and the recent findings about the influence of endotoxins in dental health, their probable mode of pathogenesis, and standard detection methods, this review analyzes the potential efficacy and benefits of probiotics in combination with conventional and contemporary treatment measures. In the oral cavity, Gram-negative bacteria are documented to predominate in the pulpal lesions with radiolucent areas and in the root canal with pulp necrosis, where they pose an absolute threat by promoting… More >

Javed Rashid^1,2, Imran Khan¹, Ghulam Ali³, Shafiq ur Rehman⁴, Fahad Alturise⁵, Tamim Alkhalifah^5,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1235-1257, 2023, DOI:10.32604/cmc.2023.032005 - 22 September 2022

Abstract The guava plant has achieved viable significance in subtropics and tropics owing to its flexibility to climatic environments, soil conditions and higher human consumption. It is cultivated in vast areas of Asian and Non-Asian countries, including Pakistan. The guava plant is vulnerable to diseases, specifically the leaves and fruit, which result in massive crop and profitability losses. The existing plant leaf disease detection techniques can detect only one disease from a leaf. However, a single leaf may contain symptoms of multiple diseases. This study has proposed a hybrid deep learning-based framework for the real-time detection… More >

Shafaq Abbas¹, Muhammad Attique Khan¹, Majed Alhaisoni², Usman Tariq³, Ammar Armghan⁴, Fayadh Alenezi⁴, Arnab Majumdar⁵, Orawit Thinnukool^6,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1139-1159, 2023, DOI:10.32604/cmc.2023.028824 - 22 September 2022

Abstract Manual diagnosis of crops diseases is not an easy process; thus, a computerized method is widely used. From a couple of years, advancements in the domain of machine learning, such as deep learning, have shown substantial success. However, they still faced some challenges such as similarity in disease symptoms and irrelevant features extraction. In this article, we proposed a new deep learning architecture with optimization algorithm for cucumber and potato leaf diseases recognition. The proposed architecture consists of five steps. In the first step, data augmentation is performed to increase the numbers of training samples.… More >

Chang Zhang¹, Ruiwen Ni¹, Ye Mu^1,2,3,4, Yu Sun^1,2,3,4,*, Thobela Louis Tyasi⁵

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 983-994, 2023, DOI:10.32604/cmc.2023.027269 - 22 September 2022

Abstract In the field of agricultural information, the identification and prediction of rice leaf disease have always been the focus of research, and deep learning (DL) technology is currently a hot research topic in the field of pattern recognition. The research and development of high-efficiency, high-quality and low-cost automatic identification methods for rice diseases that can replace humans is an important means of dealing with the current situation from a technical perspective. This paper mainly focuses on the problem of huge parameters of the Convolutional Neural Network (CNN) model and proposes a recognition model that combines More >

V. Nirmala^1,*, B. Gomathy²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2585-2601, 2023, DOI:10.32604/csse.2023.027512 - 01 August 2022

Abstract In agricultural engineering, the main challenge is on methodologies used for disease detection. The manual methods depend on the experience of the personal. Due to large variation in environmental condition, disease diagnosis and classification becomes a challenging task. Apart from the disease, the leaves are affected by climate changes which is hard for the image processing method to discriminate the disease from the other background. In Cucurbita gourd family, the disease severity examination of leaf samples through computer vision, and deep learning methodologies have gained popularity in recent years. In this paper, a hybrid method More >

Soma Prathibha^1,*, Deepak Dahiya², C. R. Rene Robin³, Cherukuru Venkata Nishkala⁴, S. Swedha⁵

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 199-214, 2023, DOI:10.32604/iasc.2023.025819 - 06 June 2022

Abstract Thyroid disease is a medical condition caused due to the excess release of thyroid hormone. It is released by the thyroid gland which is in front of the neck just below the larynx. Medical pictures such as X-rays and CT scans can, however, be used to diagnose it. In this proposed model, Deep Learning technology is used to detect thyroid diseases. A Convolution Neural Network (CNN) based modified ResNet architecture is employed to detect five different types of thyroid diseases namely 1. Hypothyroid 2. Hyperthyroid 3. Thyroid cancer 4. Thyroiditis 5. Thyroid nodules. In the… More >

Mohammad Reza Haghshenas¹, Mina Roshan Zamir¹, Mahboubeh Sadeghi¹, Mohammad Javad Fattahi¹, Kimia Mirshekari¹, Abbas Ghaderi^1,2,*

European Cytokine Network, Vol.33, No.3, pp. 54-69, 2022, DOI:10.1684/ecn.2022.0480

Abstract Interleukin-38 (IL-38) is the most recent member of the IL-1 family that acts as a natural inflammatory inhibitor by binding to cognate receptors, particularly the IL-36 receptor. In vitro, animal and human studies on autoimmune, metabolic, cardiovascular and allergic diseases, as well sepsis and respiratory viral infections, have shown that IL-38 exerts an anti-inflammatory activity by modulating the generation and function of inflammatory cytokines (e.g. IL-6, IL-8, IL-17 and IL-36) and regulating dendritic cells, M2 macrophages and regulatory T cells (Tregs). Accordingly, IL-38 may possess therapeutic potential for these types of diseases. IL-38 down-regulates CCR3+… More >