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  • Open Access

    ARTICLE

    A Drone-Based Blood Donation Approach Using an Ant Colony Optimization Algorithm

    Sana Abbas1, Faraha Ashraf1, Fahd Jarad2,3,*, Muhammad Shoaib Sardar1, Imran Siddique4

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1917-1930, 2023, DOI:10.32604/cmes.2023.024700

    Abstract This article presents an optimized approach of mathematical techniques in the medical domain by manoeuvring the phenomenon of ant colony optimization algorithm (also known as ACO). A complete graph of blood banks and a path that covers all the blood banks without repeating any link is required by applying the Travelling Salesman Problem (often TSP). The wide use promises to accelerate and offers the opportunity to cultivate health care, particularly in remote or unmerited environments by shrinking lab testing reversal times, empowering just-in-time lifesaving medical supply. More >

  • Open Access

    ARTICLE

    A Novel Meta-Heuristic Optimization Algorithm in White Blood Cells Classification

    Khaled A. Fathy, Humam K. Yaseen*, Mohammad T. Abou-Kreisha, Kamal A. ElDahshan

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1527-1545, 2023, DOI:10.32604/cmc.2023.036322

    Abstract Some human diseases are recognized through of each type of White Blood Cell (WBC) count, so detecting and classifying each type is important for human healthcare. The main aim of this paper is to propose a computer-aided WBCs utility analysis tool designed, developed, and evaluated to classify WBCs into five types namely neutrophils, eosinophils, lymphocytes, monocytes, and basophils. Using a computer-artificial model reduces resource and time consumption. Various pre-trained deep learning models have been used to extract features, including AlexNet, Visual Geometry Group (VGG), Residual Network (ResNet), which belong to different taxonomy types of deep learning architectures. Also, Binary Border… More >

  • Open Access

    ARTICLE

    Automated Artificial Intelligence Empowered White Blood Cells Classification Model

    Mohammad Yamin1, Abdullah M. Basahel1, Mona Abusurrah2, Sulafah M Basahel3, Sachi Nandan Mohanty4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 409-425, 2023, DOI:10.32604/cmc.2023.032432

    Abstract White blood cells (WBC) or leukocytes are a vital component of the blood which forms the immune system, which is accountable to fight foreign elements. The WBC images can be exposed to different data analysis approaches which categorize different kinds of WBC. Conventionally, laboratory tests are carried out to determine the kind of WBC which is erroneous and time consuming. Recently, deep learning (DL) models can be employed for automated investigation of WBC images in short duration. Therefore, this paper introduces an Aquila Optimizer with Transfer Learning based Automated White Blood Cells Classification (AOTL-WBCC) technique. The presented AOTL-WBCC model executes… More >

  • Open Access

    ARTICLE

    Blood Vessel Segmentation with Classification Model for Diabetic Retinopathy Screening

    Abdullah O. Alamoudi1,*, Sarah Mohammed Allabun2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2265-2281, 2023, DOI:10.32604/cmc.2023.032429

    Abstract Biomedical image processing is finding useful in healthcare sector for the investigation, enhancement, and display of images gathered by distinct imaging technologies. Diabetic retinopathy (DR) is an illness caused by diabetes complications and leads to irreversible injury to the retina blood vessels. Retinal vessel segmentation techniques are a basic element of automated retinal disease screening system. In this view, this study presents a novel blood vessel segmentation with deep learning based classification (BVS-DLC) model for DR diagnosis using retinal fundus images. The proposed BVS-DLC model involves different stages of operations such as preprocessing, segmentation, feature extraction, and classification. Primarily, the… More >

  • Open Access

    ARTICLE

    Hemodynamic Analysis and Diagnosis Based on Multi-Deep Learning Models

    Xing Deng1,2, Feipeng Da1,*, Haijian Shao2,3

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1369-1383, 2023, DOI:10.32604/fdmp.2023.024836

    Abstract This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional techniques. The work is intended to improve current methods for the assessment of human health through measurement of the distribution of four types of blood cells, namely, eosinophils, neutrophils, monocytes, and lymphocytes, known for their relationship with human body damage, inflammatory regions, and organ illnesses, in particular, and with the health of the immune system and other hazards, such as cardiovascular disease or infections, more in general. The results… More > Graphic Abstract

    Hemodynamic Analysis and Diagnosis Based on Multi-Deep Learning Models

  • Open Access

    ARTICLE

    Automated White Blood Cell Disease Recognition Using Lightweight Deep Learning

    Abdullah Alqahtani1, Shtwai Alsubai1, Mohemmed Sha1,*, Muhammad Attique Khan2, Majed Alhaisoni3, Syed Rameez Naqvi2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 107-123, 2023, DOI:10.32604/csse.2023.030727

    Abstract White blood cells (WBC) are immune system cells, which is why they are also known as immune cells. They protect the human body from a variety of dangerous diseases and outside invaders. The majority of WBCs come from red bone marrow, although some come from other important organs in the body. Because manual diagnosis of blood disorders is difficult, it is necessary to design a computerized technique. Researchers have introduced various automated strategies in recent years, but they still face several obstacles, such as imbalanced datasets, incorrect feature selection, and incorrect deep model selection. We proposed an automated deep learning… More >

  • Open Access

    REVIEW

    Current Perspectives on Umbilical Cord Abnormalities Including Blood Flow Parameters Based on Ultrasound Observations

    Xue Song1,2, Cun Liu2, Jingying Wang1,*, Xinglian Yang1, Mingrui Li1

    Molecular & Cellular Biomechanics, Vol.19, No.4, pp. 209-219, 2022, DOI:10.32604/mcb.2022.026082

    Abstract The umbilical cord is a vital structure between the fetus and placenta for the growth and well-being of the fetus. Although the umbilical cord may be the only organ that dies at the beginning of life, it is one of the most important parts of the feta-placental unit and plays a role in determining how life begins. In general, the prenatal examination of the umbilical cord is limited to the observation of the number of vessels and the evaluation of umbilical artery blood flow parameters. Pathologists have done more research on the morphological characteristics of the umbilical cord and linked… More >

  • Open Access

    ARTICLE

    Modeling Drug Concentration in Blood through Caputo-Fabrizio and Caputo Fractional Derivatives

    Muath Awadalla1,*, Kinda Abuasbeh1, Yves Yannick Yameni Noupoue2, Mohammed S. Abdo3

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2767-2785, 2023, DOI:10.32604/cmes.2023.024036

    Abstract This study focuses on the dynamics of drug concentration in the blood. In general, the concentration level of a drug in the blood is evaluated by the mean of an ordinary and first-order differential equation. More precisely, it is solved through an initial value problem. We proposed a new modeling technique for studying drug concentration in blood dynamics. This technique is based on two fractional derivatives, namely, Caputo and Caputo-Fabrizio derivatives. We first provided comprehensive and detailed proof of the existence of at least one solution to the problem; we later proved the uniqueness of the existing solution. The proof… More >

  • Open Access

    REVIEW

    Regulation of pathological blood-brain barrier for intracranial enhanced drug delivery and anti-glioblastoma therapeutics

    KAI WANG2,#, FENGTIAN ZHANG1,3,4,#, CHANGLONG WEN5, ZHIHUA HUANG6, ZHIHAO HU1, YUWEN ZHANG1, FUQIANG HU2,*, LIJUAN WEN1,6,*

    Oncology Research, Vol.29, No.5, pp. 351-363, 2021, DOI:10.32604/or.2022.025696

    Abstract The blood-brain barrier (BBB) is an essential component in regulating and maintaining the homeostatic microenvironment of the central nervous system (CNS). During the occurrence and development of glioblastoma (GBM), BBB is pathologically destroyed with a marked increase in permeability. Due to the obstruction of the BBB, current strategies for GBM therapeutics still obtain a meager success rate and may lead to systemic toxicity. Moreover, chemotherapy could promote pathological BBB functional restoration, which results in significantly reduced intracerebral transport of therapeutic agents during multiple administrations of GBM and the eventual failure of GBM chemotherapy. The effective delivery of intracerebral drugs still… More >

  • Open Access

    ARTICLE

    Textile UWB 5G Antenna for Human Blood Clot Measurement

    K. Sugapriya*, S. Omkumar

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 803-818, 2023, DOI:10.32604/iasc.2023.032163

    Abstract The antenna plays an essential role in the medical industry. The short-range 5th Generation (5G) communication can be used for seamless transmission, reception, patient monitoring, sensing and measuring various processes at high speeds. A passive Ultra Wide Band (UWB) antenna, used as a sensor in the measurement of Prothrombin Time (PT) i.e., blood clot is being proposed. The investigated micro-strip patch UWB antenna operating in the frequency range of 3.1 to 10.6 GHz consists of a circular patch with a diamond-shaped slot made of jeans substrate material with good sensing properties is accomplished by adjusting the copper thickness of the… More >

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