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  • Open Access

    REVIEW

    A Review of Knowledge Graph in Traditional Chinese Medicine: Analysis, Construction, Application and Prospects

    Xiaolong Qu1,2,3, Ziwei Tian1,3, Jinman Cui1,3, Ruowei Li1,3, Dongmei Li1,3,*, Xiaoping Zhang2,*

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3583-3616, 2024, DOI:10.32604/cmc.2024.055671 - 19 December 2024

    Abstract As an advanced data science technology, the knowledge graph systematically integrates and displays the knowledge framework within the field of traditional Chinese medicine (TCM). This not only contributes to a deeper comprehension of traditional Chinese medical theories but also provides robust support for the intelligent decision systems and medical applications of TCM. Against this backdrop, this paper aims to systematically review the current status and development trends of TCM knowledge graphs, offering theoretical and technical foundations to facilitate the inheritance, innovation, and integrated development of TCM. Firstly, we introduce the relevant concepts and research status… More >

  • Open Access

    ARTICLE

    Transforming Healthcare: AI-NLP Fusion Framework for Precision Decision-Making and Personalized Care Optimization in the Era of IoMT

    Soha Rawas1, Cerine Tafran1, Duaa AlSaeed2, Nadia Al-Ghreimil2,*

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4575-4601, 2024, DOI:10.32604/cmc.2024.055307 - 19 December 2024

    Abstract In the rapidly evolving landscape of healthcare, the integration of Artificial Intelligence (AI) and Natural Language Processing (NLP) holds immense promise for revolutionizing data analytics and decision-making processes. Current techniques for personalized medicine, disease diagnosis, treatment recommendations, and resource optimization in the Internet of Medical Things (IoMT) vary widely, including methods such as rule-based systems, machine learning algorithms, and data-driven approaches. However, many of these techniques face limitations in accuracy, scalability, and adaptability to complex clinical scenarios. This study investigates the synergistic potential of AI-driven optimization techniques and NLP applications in the context of the… More >

  • Open Access

    ARTICLE

    A Multilayer Network Constructed for Herb and Prescription Efficacy Analysis

    Xindi Huang1, Liwei Liang1, Sakirin Tam2, Hao Liang3, Xiong Cai4, Changsong Ding1,5,*

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 691-704, 2024, DOI:10.32604/csse.2022.029970 - 20 May 2024

    Abstract Chinese Medicine (CM) has been widely used as an important avenue for disease prevention and treatment in China especially in the form of CM prescriptions combining sets of herbs to address patients’ symptoms and syndromes. However, the selection and compatibility of herbs are complex and abstract due to intrinsic relationships between herbal properties and their overall functions. Network analysis is applied to demonstrate the complex relationships between individual herbal efficacy and the overall function of CM prescriptions. To illustrate their connections and correlations, prescription function (PF), prescription herb (PH), and herbal efficacy (HE) intra-networks are… More >

  • Open Access

    ARTICLE

    RoBGP: A Chinese Nested Biomedical Named Entity Recognition Model Based on RoBERTa and Global Pointer

    Xiaohui Cui1,2,#, Chao Song1,2,#, Dongmei Li1,2,*, Xiaolong Qu1,2, Jiao Long1,2, Yu Yang1,2, Hanchao Zhang3

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3603-3618, 2024, DOI:10.32604/cmc.2024.047321 - 26 March 2024

    Abstract Named Entity Recognition (NER) stands as a fundamental task within the field of biomedical text mining, aiming to extract specific types of entities such as genes, proteins, and diseases from complex biomedical texts and categorize them into predefined entity types. This process can provide basic support for the automatic construction of knowledge bases. In contrast to general texts, biomedical texts frequently contain numerous nested entities and local dependencies among these entities, presenting significant challenges to prevailing NER models. To address these issues, we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer… More >

  • Open Access

    ARTICLE

    Developing risk models and subtypes of autophagy-associated LncRNAs for enhanced prognostic prediction and precision in therapeutic approaches for liver cancer patients

    LU ZHANG*, JINGUO CHU*, YUSHAN YU

    Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988 - 20 March 2024

    Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using… More >

  • Open Access

    ARTICLE

    Improving Prediction of Chronic Kidney Disease Using KNN Imputed SMOTE Features and TrioNet Model

    Nazik Alturki1, Abdulaziz Altamimi2, Muhammad Umer3,*, Oumaima Saidani1, Amal Alshardan1, Shtwai Alsubai4, Marwan Omar5, Imran Ashraf6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3513-3534, 2024, DOI:10.32604/cmes.2023.045868 - 11 March 2024

    Abstract Chronic kidney disease (CKD) is a major health concern today, requiring early and accurate diagnosis. Machine learning has emerged as a powerful tool for disease detection, and medical professionals are increasingly using ML classifier algorithms to identify CKD early. This study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California, UC Irvine Machine Learning repository. The research introduces TrioNet, an ensemble model combining extreme gradient boosting, random forest, and extra tree classifier, which excels in providing highly accurate predictions for CKD. Furthermore, K nearest neighbor (KNN) More >

  • Open Access

    REVIEW

    Mesenchymal stem cells and the angiogenic regulatory network with potential incorporation and modification for therapeutic development

    VAN THI TUONG NGUYEN1,2, KHUONG DUY PHAM1,2,3, HUONG THI QUE CAO1,2, PHUC VAN PHAM1,2,*

    BIOCELL, Vol.48, No.2, pp. 173-189, 2024, DOI:10.32604/biocell.2023.043664 - 23 February 2024

    Abstract Mesenchymal stem cells (MSCs) have been proposed in regenerative medicine, especially for angiogenic purposes, due to their potential to self-renew, differentiate, and regulate the microenvironment. Peripheral vascular diseases, which are associated with reduced blood supply, have been treated but not cured. An effective therapy is to recover blood supply via vessel regeneration in the affected area, and MSCs appear to be promising for such conditions. Several studies aimed to explore the role of MSCs in performing angiogenesis and have revealed numerous potential methods to enhance MSC capacity in vessel formation. Efforts have been made to More > Graphic Abstract

    Mesenchymal stem cells and the angiogenic regulatory network with potential incorporation and modification for therapeutic development

  • Open Access

    ARTICLE

    Folic Acid-Functionalized Nanocrystalline Cellulose as a Renewable and Biocompatible Nanomaterial for Cancer-Targeting Nanoparticles

    Thean Heng Tan1, Najihah Mohd Hashim2, Wageeh Abdulhadi Yehya Dabdawb1, Mochamad Zakki Fahmi3,*, Hwei Voon Lee1,*

    Journal of Renewable Materials, Vol.12, No.1, pp. 29-43, 2024, DOI:10.32604/jrm.2023.043449 - 23 January 2024

    Abstract The study focuses on the development of biocompatible and stable FA-functionalized nanocrystalline cellulose (NCC) as a potential drug delivery system for targeting folate receptor-positive cancer cells. The FA-functionalized NCCs were synthesized through a series of chemical reactions, resulting in nanoparticles with favorable properties for biomedical applications. The microstructural analysis revealed that the functionalized NCCs maintained their rod-shaped morphology and displayed hydrodynamic diameters suitable for evading the mononuclear phagocytic system while being large enough to target tumor tissues. Importantly, these nanoparticles possessed a negative surface charge, enhancing their stability and repelling potential aggregation. The binding specificity… More > Graphic Abstract

    Folic Acid-Functionalized Nanocrystalline Cellulose as a Renewable and Biocompatible Nanomaterial for Cancer-Targeting Nanoparticles

  • Open Access

    ARTICLE

    Real-Time Remote-Mentored Echocardiography in Management of Newborns with Critical Congenital Heart Defects

    Håvard Bjerkeseth Solvin1,2,5,*, Simone Goa Diab1,4, Ole Jakob Elle2,3, Henrik Holmstrøm1,4, Henrik Brun2,4,*

    Congenital Heart Disease, Vol.18, No.5, pp. 551-559, 2023, DOI:10.32604/chd.2023.031537 - 10 November 2023

    Abstract Background: The management of suspected critical congenital heart defects (CCHD) relies on timely echocardiographic diagnosis. The availability of experienced echocardiographers is limited or even non-existent in many hospitals with obstetric units. This study evaluates remote-mentored echocardiography performed by physicians without experience in imaging of congenital heart defects (CHD). Methods: The setup included a pediatric cardiologist in a separate room, guiding a physician without experience in echocardiographic imaging of CHD in the examination of a symptomatic newborn. This remote-mentoring pair was blinded to the diagnosis of the newborn and presented with a simplified patient history. The echocardiographic… More > Graphic Abstract

    Real-Time Remote-Mentored Echocardiography in Management of Newborns with Critical Congenital Heart Defects

  • 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 - 08 November 2023

    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… More > Graphic Abstract

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

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