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Search Results (9)
  • Open Access


    Real-Time Multi-Class Infection Classification for Respiratory Diseases

    Ahmed ElShafee1, Walid El-Shafai2, Abdulaziz Alarifi3,*, Mohammed Amoon3, Aman Singh4, Moustafa H. Aly5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4157-4177, 2022, DOI:10.32604/cmc.2022.028847

    Abstract Real-time disease prediction has emerged as the main focus of study in the field of computerized medicine. Intelligent disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable, consistent, and timely, successfully lowering mortality rates, particularly during endemics and pandemics. To prevent this pandemic’s rapid and widespread, it is vital to quickly identify, confine, and treat affected individuals. The need for auxiliary computer-aided diagnostic (CAD) systems has grown. Numerous recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 virus. Utilizing advanced convolutional neural network (CNN) architectures in conjunction with radiological… More >

  • Open Access


    SARS-CoV-2 induced myocarditis: Current knowledge about its molecular and pathophysiological mechanisms


    BIOCELL, Vol.46, No.8, pp. 1779-1788, 2022, DOI:10.32604/biocell.2022.020009

    Abstract The existence of an inflammatory process in the heart muscle, related to a progressive worsening of myocardial function, different etiopathogenetic mechanisms concur and often overlap, thus making the diagnosis and the therapeutic approach complex. As the COVID-19 pandemic progresses, the effects of the disease on the organ systems and in particular on the cardiovascular system are becoming more and more profound. Cardiac involvement is a well-known event with a high percentage of findings in the heart’s magnetic field, even in asymptomatic areas. There are numerous uncertainties regarding their evolution, in the long and short term, due not only to a… More >

  • Open Access


    A Novel COVID-19 Prediction Model with Optimal Control Rates

    Ashraf Ahmed1, Yousef AbuHour2,*, Ammar El-Hassan1

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 979-990, 2022, DOI:10.32604/iasc.2022.020726

    Abstract The Corona (COVID-19) epidemic has triggered interest in many fields of technology, medicine, science, and politics. Most of the mathematical research in this area focused on analyzing the dynamics of the spread of the virus. In this article, after a review of some current methodologies, a non-linear system of differential equations is developed to model the spread of COVID-19. In order to consider a wide spectrum of scenarios, we propose a susceptible-exposed-infected-quarantined-recovered (SEIQRS)-model which was analyzed to determine threshold conditions for its stability, and the number of infected cases that is an infected person will transmit on a virus to,… More >

  • Open Access


    Gastrointestinal Tract Infections Classification Using Deep Learning

    Muhammad Ramzan1, Mudassar Raza1, Muhammad Sharif1, Muhammad Attique Khan2, Yunyoung Nam3,*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3239-3257, 2021, DOI:10.32604/cmc.2021.015920

    Abstract Automatic gastrointestinal (GI) tract disease recognition is an important application of biomedical image processing. Conventionally, microscopic analysis of pathological tissue is used to detect abnormal areas of the GI tract. The procedure is subjective and results in significant inter-/intra-observer variations in disease detection. Moreover, a huge frame rate in video endoscopy is an overhead for the pathological findings of gastroenterologists to observe every frame with a detailed examination. Consequently, there is a huge demand for a reliable computer-aided diagnostic system (CADx) for diagnosing GI tract diseases. In this work, a CADx was proposed for the diagnosis and classification of GI… More >

  • Open Access


    Multiclass Stomach Diseases Classification Using Deep Learning Features Optimization

    Muhammad Attique Khan1, Abdul Majid1, Nazar Hussain1, Majed Alhaisoni2, Yu-Dong Zhang3, Seifedine Kadry4, Yunyoung Nam5,*

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3381-3399, 2021, DOI:10.32604/cmc.2021.014983

    Abstract In the area of medical image processing, stomach cancer is one of the most important cancers which need to be diagnose at the early stage. In this paper, an optimized deep learning method is presented for multiple stomach disease classification. The proposed method work in few important steps—preprocessing using the fusion of filtering images along with Ant Colony Optimization (ACO), deep transfer learning-based features extraction, optimization of deep extracted features using nature-inspired algorithms, and finally fusion of optimal vectors and classification using Multi-Layered Perceptron Neural Network (MLNN). In the feature extraction step, pre-trained Inception V3 is utilized and retrained on… More >

  • Open Access


    Impact of Temperature on Upper Respiratory Tract Infections in Lanzhou Based on the Distributed Lag Model

    Guangyu Zhai1,2, Kuan Zhang2, Guorong Chai1,*

    Molecular & Cellular Biomechanics, Vol.18, No.1, pp. 21-31, 2021, DOI:10.32604/mcb.2021.014287

    Abstract The study mainly analyzed the relationship between temperature and the upper respiratory tract infections (URI) in Lanzhou. We collected the daily URI and meteorological data from 2010 to 2015. A distributed lag non-linear model was used to examine the relationship and potential effects of different temperatures and different lag days on the morbidity of URI. The results showed that the morbidity of URI was significantly related to the meteorological factors, and the peak of the onset of the disease usually occurred between November and February the next year. The correlation analysis was carried out between meteorological factors and URI cases,… More >

  • Open Access


    Changes in Phyto-Chemical Status upon Viral Infections in Plant: A Critical Review

    Tehmina Bahar1,*, Adeeba Mahboob Qureshi1, Fasiha Qurashi1,2, Muniba Abid1, Misbah Batool Zahra1, Muhammad Saleem Haider1

    Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 75-86, 2021, DOI:10.32604/phyton.2020.010597

    Abstract Most damaging plant diseases have been caused by viruses in the entire world. In tropical and subtropical areas, the damage caused by plant virus leads to great economic and agricultural losses. Single stranded DNA viruses (geminiviruses) are the most perilous pathogens which are responsible for major diseases in agronomic and horticultural crops. Significantly begomoviruses and mastreviruses are the biggest genus of plant infecting viruses, transmitted though Bemisia tabaci and members of Cicadellidae respectively. Plants possesses some naturally existing chemicals term as phyto-chemicals which perform important functions in the plant. Some antioxidant enzymes are used by plants for self-defense upon foreign… More >

  • Open Access


    Health care‐associated infections are associated with increased length of stay and cost but not mortality in children undergoing cardiac surgery

    Sarah Tweddell, Rohit S. Loomba, David S. Cooper, Alexis L. Benscoter

    Congenital Heart Disease, Vol.14, No.5, pp. 785-790, 2019, DOI:10.1111/chd.12779

    Abstract Introduction: Health care‐associated infections (HAIs) increase mortality, length of stay, and cost in hospitalized patients. The incidence of and risk factors for developing HAIs in the pediatric population after cardiac surgery have been studied. This study evaluates the impact of HAIs on length of stay, inpatient mortality, and cost of hospitalization in the pediatric population after cardiac surgery.
    Methods: TheKids’InpatientDatabasewasqueriedforanalysis.Patientsunder18years of age who underwent cardiac surgery from 1997 to 2012 were included. HAIs were defined as central line‐associated blood stream infections, catheter‐associated urinary tract infections, ventilator‐associated pneumonias, and surgical wound infections. Univariate analysis compared admissions with and without a HAI.… More >

  • Open Access


    Safflower (Carthamus Tinctorius L.) a Potential Source of Drugs against Cryptococcal Infections, Malaria and Leishmaniasis

    Aknur Turgumbayeva1,2, Gulbaram Ustenova1, Ubaidilla Datkhayev1, Khairolla Rahimov3, Silvijus Abramavicius4,5, Agile Tunaityte4,*, Kairat Zhakipbekov1,6, Kaldanay Kozhanova1, Saken Tulemissov7, OzikhanUstenova8, Gulmira Datkayeva9, Edgaras Stankevicius1,10

    Phyton-International Journal of Experimental Botany, Vol.89, No.1, pp. 137-146, 2020, DOI:10.32604/phyton.2020.07665

    Abstract In this research we present that Carthamus Tinctorius L. (gen. Asteraceae, otherwise known as Safflower) (Fig. 1) may contain agents active in Cryptococcal infections, malaria and Leishmaniasis, as treatment options are becoming scarce due to drug resistance development. Phytochemistry and pharmacological activities (antimicrobial, antimalarial, antileishmanial) of C. tinctorius L. were analyzed. The composition of volatile oil of safflower dried flowers was analyzed by gas chromatography-mass spectrophotometry with flame ionization detector (GC-FID) and in vitro sensitivity assays were performed to assess biological activity. 8 known and 3 unknown compounds were detected in the extract (Fig. 1). Then the Safflower ointment was… More >

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