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  • Open Access

    ARTICLE

    Chimp Optimization Algorithm Based Feature Selection with Machine Learning for Medical Data Classification

    Firas Abedi1, Hayder M. A. Ghanimi2, Abeer D. Algarni3, Naglaa F. Soliman3,*, Walid El-Shafai4,5, Ali Hashim Abbas6, Zahraa H. Kareem7, Hussein Muhi Hariz8, Ahmed Alkhayyat9

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

    Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

  • Open Access

    REVIEW

    The bacterial small RNAs: The new biomarkers of oral microbiota-associated cancers and diseases

    MENGYING MAO1,2,3,#, TING DONG1,2,3,#, YANJING LIANG3,4, KEYONG YUAN1,2,3, QIAOQIAO JIN1,2,3, PENGFEI ZHANG1,2,3, ZHENGWEI HUANG1,2,3,*

    BIOCELL, Vol.47, No.10, pp. 2187-2193, 2023, DOI:10.32604/biocell.2023.042357

    Abstract The oral microbiota is a vital part of the human microbiota that functions in various physiological processes and is highly relevant to cancers and other diseases. With the alterations of host immune competence, the homeostatic balance existing between the oral microbiota and host may be disturbed and result in the development of diseases. Numerous observations have suggested that small RNAs are key regulators of bacterial pathogenesis and bacteria-host interactions. Further, bacterial small RNAs are considered to be promising biomarkers for the development of novel, and efficacious therapies for oral dysbiosis. Mechanistic insights into how oral pathogens communicate with other bacteria… More > Graphic Abstract

    The bacterial small RNAs: The new biomarkers of oral microbiota-associated cancers and diseases

  • Open Access

    REVIEW

    Cancer-associated fibroblasts of colorectal cancer: Translational prospects in liquid biopsy and targeted therapy

    ELYN AMIELA SALLEH1, YEONG YEH LEE2, ANDEE DZULKARNAEN ZAKARIA3, NUR ASYILLA CHE JALIL4, MARAHAINI MUSA1,*

    BIOCELL, Vol.47, No.10, pp. 2233-2244, 2023, DOI:10.32604/biocell.2023.030541

    Abstract Colorectal cancer (CRC) is a major global health concern. Accumulation of cancer-associated fibroblasts (CAFs) in CRC is associated with poor prognosis and disease recurrence. CAFs are the main cellular component of the tumor microenvironment. CAF-tumor cell interplay, which is facilitated by various secretomes, drives colorectal carcinogenesis. The complexity of CAF populations contributes to the heterogeneity of CRC and influences patient survival and treatment response. Due to their significant roles in colorectal carcinogenesis, different clinical applications utilizing or targeting CAFs have been suggested. Circulating CAFs (cCAFs) which can be detected in blood samples, have been proposed to help in determining patient… More > Graphic Abstract

    Cancer-associated fibroblasts of colorectal cancer: Translational prospects in liquid biopsy and targeted therapy

  • Open Access

    Ring finger protein 157 is a prognostic biomarker and is associated with immune infiltrates in human breast cancer

    XIN ZHU1,2,#, BIN XIAO3,#,*, WENWU ZHANG3,4, XIAOYU SONG3, WEI GONG5, LINHAI LI3,*, XINPING CHEN1,2,*

    BIOCELL, Vol.47, No.10, pp. 2265-2281, 2023, DOI:10.32604/biocell.2023.029195

    Abstract Background: The protein encoded by ring finger protein 157 (RNF157) is known to function as an E3 ubiquitin ligase. However, whether the level of RNF157 expression in breast cancer correlates with prognosis and immune cell infiltration among breast cancer patients remains to be further explored. Methods: In this study, publicly available datasets were used for evaluating RNF157 expression in different tumors compared with normal samples. Several independent datasets were screened for investigating the relationship between RNF157 and breast cancer survival, different mutation profiles, and tumor immune cell infiltration. We conducted a pathway enrichment analysis to identify signaling pathways associated with… More >

  • Open Access

    ARTICLE

    DFE-GCN: Dual Feature Enhanced Graph Convolutional Network for Controversy Detection

    Chengfei Hua1,2,3, Wenzhong Yang2,3,*, Liejun Wang2,3, Fuyuan Wei2,3, KeZiErBieKe HaiLaTi2,3, Yuanyuan Liao2,3

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 893-909, 2023, DOI:10.32604/cmc.2023.040862

    Abstract With the development of social media and the prevalence of mobile devices, an increasing number of people tend to use social media platforms to express their opinions and attitudes, leading to many online controversies. These online controversies can severely threaten social stability, making automatic detection of controversies particularly necessary. Most controversy detection methods currently focus on mining features from text semantics and propagation structures. However, these methods have two drawbacks: 1) limited ability to capture structural features and failure to learn deeper structural features, and 2) neglecting the influence of topic information and ineffective utilization of topic features. In light… More >

  • Open Access

    ARTICLE

    Intelligent Service Search Model Using Emerging Technologies

    Farhan Amin, Gyu Sang Choi*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1165-1181, 2023, DOI:10.32604/cmc.2023.040693

    Abstract In recent years, the Internet of Things (IoT) has played a vital role in providing various services to users in a smart city. However, searching for services, objects, data, and frameworks remains a concern. The technological advancements in Cyber-Physical Systems (CPSs) and the Social Internet of Things (SIoT) open a new era of research. Thus, we propose a Cyber-Physical-Social Systems (CPSs) for service search. Herein, service search and object discovery operation carries with the suitable selection of friends in the network. Our proposed model constructs a graph and performs social network analysis (SNA). We suggest degree centrality, clustering, and scale-free… More >

  • Open Access

    ARTICLE

    Break Free from Depression: Implementation and Outcomes of a School-Based Depression Awareness Program

    Amy J. Kaye1,*, Vanessa Prosper2, Kathryn Moffa1, Vanja Pejic1, Karen Capraro1, Georgios D. Sideridis1, Abigail Ross1,3, Kristine M. Dennery1, David R. DeMaso1

    International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1103-1115, 2023, DOI:10.32604/ijmhp.2023.030185

    Abstract The objective of this study was to evaluate the impact of Break Free from Depression (BFFD), a school-based depression awareness curriculum, in comparison to a wait list control group. A total of 13 eighth grade classrooms participated in either an intervention or control group and completed pre-, post-, and three-month follow-up surveys. Students participating in BFFD (N = 6 classrooms, 166 students) demonstrated enhanced knowledge of and more adaptive attitudes towards depression compared to the control group (N = 7 classrooms, 155 students). Participants in the BFFD intervention also demonstrated increases in their confidence in knowing how to seek help… More >

  • Open Access

    ARTICLE

    Preventing Health Anxiety: The Role of Self-Evaluation, Sense of Coherence, Self-Rated Health and Perceived Social Support

    Sándor Csibi1, Mónika Csibi2,*, József Bognár1

    International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1081-1088, 2023, DOI:10.32604/ijmhp.2023.029390

    Abstract Background: Components of Self, completed with the perceived social support determine the individual differences in the evaluation of a stressor and the behavioral responses toward it, such as health-related anxiety. The study set as a goal the analysis of associations between the components of Self, such as self-evaluation, sense of coherence, perceived social support, and reported health-related anxiety in an adult sample. Methods: 147 adults from the 18–73 age group (mean age 37.5) voluntarily completed the questionnaire through Qualtrics online platform containing the Short Health Anxiety Inventory, Core Self-Evaluation Scale, Social Support Assessing Scale, and one Health Self-Evaluation Item. Results:More >

  • Open Access

    ARTICLE

    Detecting Phishing Using a Multi-Layered Social Engineering Framework

    Kofi Sarpong Adu-Manu*, Richard Kwasi Ahiable

    Journal of Cyber Security, Vol.5, pp. 13-32, 2023, DOI:10.32604/jcs.2023.043359

    Abstract As businesses develop and expand with a significant volume of data, data protection and privacy become increasingly important. Research has shown a tremendous increase in phishing activities during and after COVID-19. This research aimed to improve the existing approaches to detecting phishing activities on the internet. We designed a multi-layered phish detection algorithm to detect and prevent phishing applications on the internet using URLs. In the algorithm, we considered technical dimensions of phishing attack prevention and mitigation on the internet. In our approach, we merge, Phishtank, Blacklist, Blocklist, and Whitelist to form our framework. A web application system and browser… More >

  • Open Access

    ARTICLE

    Improving Sentiment Analysis in Election-Based Conversations on Twitter with ElecBERT Language Model

    Asif Khan1, Huaping Zhang1,*, Nada Boudjellal2, Arshad Ahmad3, Maqbool Khan3

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3345-3361, 2023, DOI:10.32604/cmc.2023.041520

    Abstract Sentiment analysis plays a vital role in understanding public opinions and sentiments toward various topics. In recent years, the rise of social media platforms (SMPs) has provided a rich source of data for analyzing public opinions, particularly in the context of election-related conversations. Nevertheless, sentiment analysis of election-related tweets presents unique challenges due to the complex language used, including figurative expressions, sarcasm, and the spread of misinformation. To address these challenges, this paper proposes Election-focused Bidirectional Encoder Representations from Transformers (ElecBERT), a new model for sentiment analysis in the context of election-related tweets. Election-related tweets pose unique challenges for sentiment… More >

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