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  • Open Access

    ARTICLE

    A Deep Learning Model for Insurance Claims Predictions

    Umar Isa Abdulkadir*, Anil Fernando*

    Journal on Artificial Intelligence, Vol.6, pp. 71-83, 2024, DOI:10.32604/jai.2024.045332

    Abstract One of the significant issues the insurance industry faces is its ability to predict future claims related to individual policyholders. As risk varies from one policyholder to another, the industry has faced the challenge of using various risk factors to accurately predict the likelihood of claims by policyholders using historical data. Traditional machine-learning models that use neural networks are recognized as exceptional algorithms with predictive capabilities. This study aims to develop a deep learning model using sequential deep regression techniques for insurance claim prediction using historical data obtained from Kaggle with 1339 cases and eight variables. This study adopted a… More >

  • Open Access

    ARTICLE

    An Approach for Human Posture Recognition Based on the Fusion PSE-CNN-BiGRU Model

    Xianghong Cao, Xinyu Wang, Xin Geng*, Donghui Wu, Houru An

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 385-408, 2024, DOI:10.32604/cmes.2024.046752

    Abstract This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit (PSE-CNN-BiGRU) fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home environments. Firstly, the deep convolutional network is integrated with the Mediapipe framework to extract high-precision, multi-dimensional information from the key points of the human skeleton, thereby obtaining a human posture feature set. Thereafter, a double-layer BiGRU algorithm is utilized to extract multi-layer, bidirectional temporal features from the human posture feature set, and a… More >

  • Open Access

    ARTICLE

    SIMULATION OF EMBOLIZATION PARTICLE TRAJECTORIES

    Nessa Johnson, John Abraham*, Zach Helgeson, Michael Hennessey

    Frontiers in Heat and Mass Transfer, Vol.2, No.2, pp. 1-7, 2011, DOI:10.5098/hmt.v2.2.3006

    Abstract A numerical simulation has been performed on the hemodynamics associated with embolization procedures. The flow geometry includes a multibranch artery which is upstream of a targeted tumor. During the procedure, drug-eluting particles are released into the local arterial geometry and are carried downstream by the flowing blood. The intention is to cause embolization of a daughter artery which feeds the tumor. As particles are injected into the blood stream, and as the embolization progresses, it is possible for the particulates to substantially alter the blood flow in the main artery. This alteration may lead to a maldistribution of blood flow… More >

  • Open Access

    ARTICLE

    Classification of Human Protein in Multiple Cells Microscopy Images Using CNN

    Lina Al-joudi, Muhammad Arif*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1763-1780, 2023, DOI:10.32604/cmc.2023.039413

    Abstract The subcellular localization of human proteins is vital for understanding the structure of human cells. Proteins play a significant role within human cells, as many different groups of proteins are located in a specific location to perform a particular function. Understanding these functions will help in discovering many diseases and developing their treatments. The importance of imaging analysis techniques, specifically in proteomics research, is becoming more prevalent. Despite recent advances in deep learning techniques for analyzing microscopy images, classification models have faced critical challenges in achieving high performance. Most protein subcellular images have a significant class imbalance. We use oversampling… More >

  • Open Access

    ARTICLE

    Elucidating the clinical and immunological value of m6A regulator-mediated methylation modification patterns in adrenocortical carcinoma

    WENHAO XU1,#, HAOMING LI2,#, YASIR HAMEED3, MOSTAFA A. ABDEL-MAKSOUD4, SAEEDAH MUSAED ALMUTAIRI4, AYMAN MUBARAK4, MOHAMMED AUFY5, WAEL ALTURAIKI6, ABDULAZIZ J. ALSHALANI6, AYMAN M. MAHMOUD7,*, CHEN LI8,*

    Oncology Research, Vol.31, No.5, pp. 819-831, 2023, DOI:10.32604/or.2023.029414

    Abstract N6-methyladenosine methylation (m6A) is a common type of epigenetic alteration that prominently affects the prognosis of tumor patients. However, it is unknown how the m6A regulator affects the tumor microenvironment (TME) cell infiltration in adrenocortical carcinoma (ACC) and how it affects the prognosis of ACC patients yet. The m6A alteration patterns of 112 ACC patients were evaluated, furthermore, the association with immune infiltration cell features was investigated. The unsupervised clustering method was applied to typify the m6A alteration patterns of ACC patients. The principal component analysis (PCA) technique was taken to create the m6A score to assess the alteration pattern… More >

  • Open Access

    ARTICLE

    The Relationship between Exercise and Psychotic Symptoms in College Students: A Cross-Sectional Analysis

    Yangjuan Ye, Haijun Tang*

    International Journal of Mental Health Promotion, Vol.25, No.7, pp. 873-879, 2023, DOI:10.32604/ijmhp.2023.028107

    Abstract An increasing number of studies have suggested that increased physical activity is associated with less mental illness. However, the relationship between exercise and psychotic experiences (PEs) is still unknown. The purpose of this study was to explore the relationship between exercise and PEs in college students in the United States. Data from the Health Mind Survey (2020–2021 round) were analyzed. Respondents included 137,916 college students who were asked about exercise and PEs (lifetime psychotic experiences, delusions, and hallucinations). A multivariate logistic regression analysis was used to investigate the relationship between exercise and PEs while controlling for demographic characteristics. There was… More >

  • Open Access

    ARTICLE

    3D Human Pose Estimation Using Two-Stream Architecture with Joint Training

    Jian Kang1, Wanshu Fan1, Yijing Li2, Rui Liu1, Dongsheng Zhou1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 607-629, 2023, DOI:10.32604/cmes.2023.024420

    Abstract With the advancement of image sensing technology, estimating 3D human pose from monocular video has become a hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequent action analysis and understanding. It empowers a wide spectrum of potential applications in various areas, such as intelligent transportation, human-computer interaction, and medical rehabilitation. Currently, some methods for 3D human pose estimation in monocular video employ temporal convolutional network (TCN) to extract inter-frame feature relationships, but the majority of them suffer from insufficient inter-frame feature relationship extractions. In this paper, we decompose the 3D joint location regression… More >

  • Open Access

    ARTICLE

    Improved Whale Optimization with Local-Search Method for Feature Selection

    Malek Alzaqebah1,2,*, Mutasem K. Alsmadi3, Sana Jawarneh4, Jehad Saad Alqurni5, Mohammed Tayfour3, Ibrahim Almarashdeh3, Rami Mustafa A. Mohammad6, Fahad A. Alghamdi3, Nahier Aldhafferi6, Abdullah Alqahtani6, Khalid A. Alissa7, Bashar A. Aldeeb8, Usama A. Badawi3, Maram Alwohaibi1,2, Hayat Alfagham3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1371-1389, 2023, DOI:10.32604/cmc.2023.033509

    Abstract Various feature selection algorithms are usually employed to improve classification models’ overall performance. Optimization algorithms typically accompany such algorithms to select the optimal set of features. Among the most currently attractive trends within optimization algorithms are hybrid metaheuristics. The present paper presents two Stages of Local Search models for feature selection based on WOA (Whale Optimization Algorithm) and Great Deluge (GD). GD Algorithm is integrated with the WOA algorithm to improve exploitation by identifying the most promising regions during the search. Another version is employed using the best solution found by the WOA algorithm and exploited by the GD algorithm.… More >

  • Open Access

    ARTICLE

    Innovative Fungal Disease Diagnosis System Using Convolutional Neural Network

    Tahir Alyas1,*, Khalid Alissa2, Abdul Salam Mohammad3, Shazia Asif4, Tauqeer Faiz5, Gulzar Ahmed6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4869-4883, 2022, DOI:10.32604/cmc.2022.031376

    Abstract Fungal disease affects more than a billion people worldwide, resulting in different types of fungus diseases facing life-threatening infections. The outer layer of your body is called the integumentary system. Your skin, hair, nails, and glands are all part of it. These organs and tissues serve as your first line of defence against bacteria while protecting you from harm and the sun. The It serves as a barrier between the outside world and the regulated environment inside our bodies and a regulating effect. Heat, light, damage, and illness are all protected by it. Fungi-caused infections are found in almost every… More >

  • Open Access

    ARTICLE

    A Fast Tongue Detection and Location Algorithm in Natural Environment

    Lei Zhu1, Guojiang Xin1,2,*, Xin Wang1, Changsong Ding1,2, Hao Liang1,2, Qilei Chen3

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4727-4742, 2022, DOI:10.32604/cmc.2022.028187

    Abstract The collection and extraction of tongue images has always been an important part of intelligent tongue diagnosis. At present, the collection of tongue images generally needs to be completed in a sealed, stable light environment, which is not conducive to the promotion of extensive tongue image and intelligent tongue diagnosis. In response to the problem, a new algorithm named GCYTD (GELU-CA-YOLO Tongue Detection) is proposed to quickly detect and locate the tongue in a natural environment, which can greatly reduce the restriction of the tongue image collection environment. The algorithm is based on the YOLO (You Only Look Once) V4-tiny… More >

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