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  1. 1

    Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

    Published 2022
    “…When smart contracts are used to make decisions and conduct analytics with machine-learning algorithms, the results may be trusted and unquestioned. …”
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    Systematic review on ai-blockchain based e-healthcare records management systems by Haddad, Alaa, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Hasbullah, Nurul Fadzlin, Zabidi, Suriza Ahmad

    Published 2022
    “…When smart contracts are used to make decisions and conduct analytics with machine-learning algorithms, the results may be trusted and unquestioned. …”
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  3. 3

    A systematic literature review on the application of artificial intelligence in enhancing care for kidney diseases patients by Rahman, Md Saidur, Md Nor, Nor Saadah

    Published 2024
    “…Fourteen studies published from 2018 to 2024 were reviewed in the systematic review to learn how AI technology was incorporated to improve care for CKD patients. …”
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  4. 4

    Artificial intelligence-driven anticancer peptide discovery by Wu, Junrui, Ji, Shuaiqi, Sahibzada, Kashif Iqbal, Lou, Mengxue, An, Feiyu, Li, Wenqian, Guo, Jiawei, Zhang, Taowei, Zhang, Xinyi, Chou, Yilin, Zhang, Henan, Jin, Hao, Ma, Teng, Liu, Weichi, Alikulov, Begali, Golovneva, Natalia Alekseevna, Foo, Hooi Ling, Kuralay, Issayeva, Sun, Zhihong, Wei, Dongqing, Wu, Rina

    Published 2025
    “…However, traditional screening methods are constrained by their low efficiency, high costs, and technical complexity, limiting their capacity to meet the demands of high-throughput applications. Artificial intelligence (AI) has provided new methods to address these challenges, significantly improving the efficiency and accuracy of ACP screening through the application of machine learning and deep learning algorithms. …”
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    Application of machine learning algorithms to predict removal efficiency in treating produced water via gas hydrate-based desalination by Nallakukkala, Sirisha, Tackie-Otoo, Bennet Nii, Aliyu, Ruwaida, Lal, Bhajan, Nallakukkala, Jagadish Ram Deepak, Devi, Gayathri

    Published 2025
    “…In this context. ML algorithms provide powerful data driven means to model complex relationship within experimental datasets to improve process optimisation This study systematically evaluated several supervised ML models, including Random Forest (RF) Support Vector Machines (SVM), Ridge Regression, Lasso Regression, Decision Tree, Extra Tree Regression, Gradient Boost, and XGBoost, to predict removal efficiency in GHBD system. …”
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  6. 6

    Lane detection in autonomous vehicles : A systematic review by Noor Jannah, Zakaria, Mohd Ibrahim, Shapiai, Rasli, Abd Ghani, Mohd Najib, Mohd Yassin, Mohd Zamri, Ibrahim, Nurbaiti, Wahid

    Published 2023
    “…Recent advancements imply that attention mechanism has become a popular combined strategy with deep learning methods. The use of deep algorithms in conjunction with other techniques showed promising outcomes. …”
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    Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

    Published 2023
    “…Decision trees; Forecasting; Multilayer neural networks; Ozone; Predictive analytics; Support vector machines; Artificial intelligence techniques; Machine learning techniques; Multi layer perceptron; Optimization approach; Ozone concentration forecasting; Prediction accuracy; Stand-alone algorithm; Tropospheric ozone concentration; Learning systems; ozone; air quality; algorithm; concentration (composition); machine learning; optimization; ozone; prediction; theoretical study; air pollutant; air quality; artificial intelligence; artificial neural network; concentration (parameter); decision tree; feed forward neural network; forecasting; fuzzy system; human; measurement accuracy; multilayer perceptron; prediction; random forest; recurrent neural network; Review; support vector machine; systematic review…”
    Review
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    A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

    Published 2023
    “…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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    A systematic review of machine learning techniques and applications in soil improvement using green materials by Saad, Ahmed Hassan, Nahazanan, Haslinda, Yusuf, Badronnisa, Toha, Siti Fauziah, Alnuaim, Ahmed, El-Mouchi, Ahmed, Elseknidy, Mohamed, Mohammed, Angham Ali

    Published 2023
    “…The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using a systematic procedure known as PRISMA and meta-analysis. …”
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    Trends on technologies and artificial intelligence in education for personalized learning: systematic literature review by Hashim, Suraya, Omar, Muhd Khaizer, Ab. Jalil, Habibah, Mohd Sharef, Nurfadhlina

    Published 2022
    “…To gain a better understanding of the concept and implementation of a personalized learning environment employing AI technology, a systematic literature review (SLR) was conducted to identify the trends of technologies and Artificial Intelligence in Education (AIEd) in promoting personalized learning. …”
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    A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

    Published 2023
    “…Annually, almost half a million women do not survive the disease and die from breast cancer. Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. …”
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  14. 14

    Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

    Published 2024
    “…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”
    thesis::doctoral thesis
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    The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed by Ridwan M.A., Radzi N.A.M., Azmi K.H.M., Ahmad A., Abdullah F., Ahmad W.S.H.M.W.

    Published 2024
    “…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”
    Conference Paper
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    Design of Modeling Elements of Luoshan Shadow Puppets Creative Goods Based on Deep Learning by Taotao, Xu, Musdi, Shanat, Brendan Chan, Kah Le, Wei, Zhang

    Published 2023
    “…In this paper, based on the design of modeling elements of mountain shadow puppets, the characteristics of visual elements of shadow puppets creative goods are analyzed, and an intelligent design algorithm of shadow puppets creative goods based on deep learning (DL) is innovatively proposed. …”
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    Proceeding
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    Hybrid Intelligent Warning System for Boiler tube Leak Trips by Singh, D., Ismail, F.B., Shakir Nasif, M.

    Published 2017
    “…The Extreme Learning Machine (ELM) methodology was also adopted in IWS-1 and compared with traditional training algorithms. …”
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    Application of phi (Φ), the golden ratio, in computing: a systematic review by Akhtaruzzaman, M, Tanvin, Jamal Uddin, Shafie, Amir Akramin, Shahryer, Fahim, Halder, Sachitra

    Published 2024
    “…The review also categorizes findings by their specific applications and contexts, providing valuable insights into φ’s impact on mathematics, cryptography, search algorithms, machine learning, artificial intelligence, photonics, natural sciences, system design, power engineering, robotics, and practical human life. …”
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