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  • Open Access

    ARTICLE

    An Intelligent Gestational Diabetes Diagnosis Model Using Deep Stacked Autoencoder

    A. Sumathi1,*, S. Meganathan1, B. Vijila Ravisankar2

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3109-3126, 2021, DOI:10.32604/cmc.2021.017612 - 24 August 2021

    Abstract Gestational Diabetes Mellitus (GDM) is one of the commonly occurring diseases among women during pregnancy. Oral Glucose Tolerance Test (OGTT) is followed universally in the diagnosis of GDM diagnosis at early pregnancy which is costly and ineffective. So, there is a need to design an effective and automated GDM diagnosis and classification model. The recent developments in the field of Deep Learning (DL) are useful in diagnosing different diseases. In this view, the current research article presents a new outlier detection with deep-stacked Autoencoder (OD-DSAE) model for GDM diagnosis and classification. The goal of the… More >

  • Open Access

    ARTICLE

    Game-Theory Based Graded Diagnosis Strategies of Craniocerebral Injury

    Yiming Liu1, Ke Chen1, Lanzhen Bian2, Lei Ren3, Jing Hu4,*, Jinyue Xia5

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 553-561, 2021, DOI:10.32604/iasc.2021.017391 - 11 August 2021

    Abstract Craniocerebral injury is a common surgical emergency in children. It has the highest mortality and disability rate, and the second highest incidence rate. Accidental injuries due to falls, sports and traffic accidents are the main causes of craniocerebral injury. In recent years, the incidence rate of craniocerebral injury in children has continued to rise, which injury stretches out the limited medical resources. Moreover, it is very difficult to deal with complex craniocerebral trauma in the hospital of county town, in which is not rich in medical resources because of the lack of experienced doctors and… More >

  • Open Access

    ARTICLE

    Diagnosis of Neem Leaf Diseases Using Fuzzy-HOBINM and ANFIS Algorithms

    K. K. Thyagharajan, I. Kiruba Raji*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2061-2076, 2021, DOI:10.32604/cmc.2021.017591 - 21 July 2021

    Abstract This paper proposes an approach to detecting diseases in neem leaf that uses a Fuzzy-Higher Order Biologically Inspired Neuron Model (F-HOBINM) and adaptive neuro classifier (ANFIS). India exports USD 0.28-million worth of neem leaf to the UK, USA, UAE, and Europe in the form of dried leaves and powder, both of which help reduce diabetes-related issues, cardiovascular problems, and eye disorders. Diagnosing neem leaf disease is difficult through visual interpretation, owing to similarity in their color and texture patterns. The most common diseases include bacterial blight, Colletotrichum and Alternaria leaf spot, blight, damping-off, powdery mildew,… More >

  • Open Access

    ARTICLE

    Diagnosis of Leukemia Disease Based on Enhanced Virtual Neural Network

    K. Muthumayil1, S. Manikandan2, S. Srinivasan3, José Escorcia-Gutierrez4,*, Margarita Gamarra5, Romany F. Mansour6

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2031-2044, 2021, DOI:10.32604/cmc.2021.017116 - 21 July 2021

    Abstract White Blood Cell (WBC) cancer or leukemia is one of the serious cancers that threaten the existence of human beings. In spite of its prevalence and serious consequences, it is mostly diagnosed through manual practices. The risks of inappropriate, sub-standard and wrong or biased diagnosis are high in manual methods. So, there is a need exists for automatic diagnosis and classification method that can replace the manual process. Leukemia is mainly classified into acute and chronic types. The current research work proposed a computer-based application to classify the disease. In the feature extraction stage, we… More >

  • Open Access

    ARTICLE

    Open-Circuit Faults Diagnosis in Direct-Drive PMSG Wind Turbine Converter

    Wei Zhang1,2, Qihui Ling1,2,*, Qiancheng Zhao1,2, Hushu Wu3

    Energy Engineering, Vol.118, No.5, pp. 1515-1535, 2021, DOI:10.32604/EE.2021.014162 - 16 July 2021

    Abstract The condition monitoring and fault diagnosis have been identified as the key to achieving higher availabilities of wind turbines. Numerous studies show that the open-circuit fault is a significant contributor to the failures of wind turbine converter. However, the multiple faults combinations and the influence of wind speed changes abruptly, grid voltage sags and noise interference have brought great challenges to fault diagnosis. Accordingly, concerning the open-circuit fault of converters in direct-driven PMSG wind turbine, a diagnostic method for multiple open-circuit faults is proposed in this paper, which is divided into two tasks: The first… More >

  • Open Access

    ARTICLE

    Optimization of Transducer Location for Novel Non-Intrusive Methodologies of Diagnosis in Diesel Engines

    S. Narayan1,*, M. U. Kaisan2, Shitu Abubakar2, Faisal O. Mahroogi3, Vipul Gupta4

    Sound & Vibration, Vol.55, No.3, pp. 221-234, 2021, DOI:10.32604/sv.2021.016539 - 15 July 2021

    Abstract The health monitoring has been studied to ensure integrity of design of engine structure by detection, quantification, and prediction of damages. Early detection of faults may allow the downtime of maintenance to be rescheduled, thus preventing sudden shutdown of machines. In cylinder pressure developed, vibrations and noise emissions data provide a rich source of information about condition of engines. Monitoring of vibrations and noise emissions are novel non-intrusive methodologies for which positioning of various transducers are important issue. The presented work shows applicability of these diagnosis methodologies adopted in case of diesel engines. The effects More >

  • Open Access

    ARTICLE

    COVID-19 Diagnosis Using Transfer-Learning Techniques

    Mohammed Faisal1,*, Fahad Albogamy2, Hebah ElGibreen3, Mohammed Algabri3, Syed Ahad M. Alvi1, Mansour Alsulaiman3

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 649-667, 2021, DOI:10.32604/iasc.2021.017898 - 01 July 2021

    Abstract COVID-19 was first discovered in Wuhan, China, in December 2019 and has since spread worldwide. An automated and fast diagnosis system needs to be developed for early and effective COVID-19 diagnosis. Hence, we propose two- and three-classifier diagnosis systems for classifying COVID-19 cases using transfer-learning techniques. These systems can classify X-ray images into three categories: healthy, COVID-19, and pneumonia cases. We used two X-ray image datasets (DATASET-1 and DATASET-2) collected from state-of-the-art studies and train the systems using deep learning architectures, such as VGG-19, NASNet, and MobileNet2, on these datasets. According to the validation and More >

  • Open Access

    ARTICLE

    Application Value of Multi-Slice Spiral CT Multiplanar Reconstruction Technique in the Diagnosis and Clinicopathological Analysis of Gastrointestinal Lymphoma

    Yongtao Yu, Guangdong Zou*

    Oncologie, Vol.23, No.2, pp. 293-301, 2021, DOI:10.32604/Oncologie.2021.015520 - 22 June 2021

    Abstract Objective: The purpose was to explore the value of multi-slice spiral CT (MSCT) multiplanar reconstruction technique in the diagnosis and clinicopathological analysis of gastrointestinal lymphoma (GIL). Methods: 82 GIL patients treated in our hospital from February 2018 to February 2019 were selected as the experimental group of this study, and 82 patients with other gastrointestinal tumors diagnosed by pathology during the same period were selected as the control group. Both groups of patients were scanned by MSCT and analyzed by multiplanar reconstruction technique to compare the diagnostic results and clinicopathological indexes of the two groups. Results: The… More >

  • Open Access

    ARTICLE

    Alteration of Ornithine Metabolic Pathway in Colon Cancer and Multivariate Data Modelling for Cancer Diagnosis

    Xin Hu1,2,#, Fangyu Jing3,#, Qingjun Wang1,4, Linyang Shi1, Yunfeng Cao4,5, Zhitu Zhu1,4,*

    Oncologie, Vol.23, No.2, pp. 203-217, 2021, DOI:10.32604/Oncologie.2021.016155 - 22 June 2021

    Abstract It is noteworthy that colon cancer is the fourth place in new cases and the fifth in mortalities according to global cancer statistics 2018. Tumorigenesis displays specific correlation with metabolic alterations. A variety of metabolites, including ornithine (Orn), are related to colon cancer according to sources of disease metabolic information retrieval in human metabolome database. The metabolic regulation of Orn pathway is a key link in the survival of cancer cells. In this study, the plasma Orn levels in colon cancer patients and healthy participants were measured by liquid chromatography tandem mass spectrometry, and the… More >

  • Open Access

    REVIEW

    MicroRNA in HCC: Biomarkers and Therapeutic Targets

    Zheng Wang1, Yongxia He1, Yuwei Song1, Yue Wang2, Feng Chen3,*

    Oncologie, Vol.23, No.2, pp. 177-184, 2021, DOI:10.32604/Oncologie.2021.014773 - 22 June 2021

    Abstract Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality. At present, diagnostic methods such as imaging observation, serum testing and tissue biopsy, as well as treatment methods such as surgical resection, radiotherapy, and chemotherapy have certain limitations in clinical interventions for HCC due to the complex pathogenesis and drug resistance of liver cancer, which seriously affect the survival and prognosis of patients. As a large-scale cytokine, microRNA (miRNA) plays an important role in regulating various life activities of cells. Extensive evidence proved that certain miRNAs are specifically expressed in the tissues and More >

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