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An efficient and effective case classification method based on slicing
Published 2006“…The algorithms are: Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5). …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…The development of Management Information Systems (MIS) is impossible without the use of machine learning (ML). It's a type of Artificial Intelligence (AI) that makes predictions using statistical models. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…The study involved three machine learning algorithms, random forest (RF), extra tree (ET), and support vector machine (SVM). …”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results
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Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model
Published 2025“…This study, using advanced text mining and multiple deep learning algorithms, utilized the Web of Science for scientific papers (1587) and the Derwent innovations index for patents (1314) from 2018 to 2022 to study future trends of emerging AI in healthcare. …”
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Neutralisation state driven single-agent search strategy for solving constraint satisfaction problem / Saajid Akram Ahmed Abuluaih
Published 2019“…Since Constraint Satisfaction Problem (CSP) is an NP-complete problem, brute-force search algorithms such as Backtracking algorithm (BT) are required as the guarantee to find a solution, when there is one. …”
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Revolutionising pharmacy through machine learning: the progress and perils / Yuslina Zakaria
Published 2024“…ML, a branch of artificial intelligence (AI), uses algorithms such as neural networks, decision trees, and support vector machines to learn from large datasets and make predictions. …”
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Comparative analysis of danger theory variants in measuring risk level for text spam messages
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Systematic review on ai-blockchain based e-healthcare records management systems
Published 2022“…AI algorithms rely on data or information to learn, analyze, and reach conclusions. …”
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Prescription: Issue No. 7 (July 2024)
Published 2024“…ML, a branch of artificial intelligence (AI), uses algorithms such as neural networks, decision trees, and support vector machines to learn from large datasets and make predictions. …”
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Systematic review on ai-blockchain based e-healthcare records management systems
Published 2022“…AI algorithms rely on data or information to learn, analyze, and reach conclusions. …”
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Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate
Published 2025“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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Modelling and optimization of microhardness of electroless Ni-P-TiO2composite coating based on machine learning approaches and RSM
Published 2021“…The microhardness of the electroless Ni-P-TiO2 coated composite was measured and predicted by various machine learning algorithms. The recorded datasets were used for optimization by Response Surface Methodology (RSM) model whereas, training and testing of the four different Artificial Intelligence (AI) models were executed using machine learning methods. …”
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Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin
Published 2023“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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