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181
Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features
Published 2024“…This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. …”
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182
Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks
Published 2024“…Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. …”
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183
Artificial Intelligence and Machine Learning Applications in Sudden Cardiac Arrest Prediction and Management: A Comprehensive Review
Published 2023“…There’s a significant focus on the integration of AI and ML in prehospital emergency care, particularly in using ML algorithms for predicting outcomes in COVID-19 patients and enhancing the recognition of out-of-hospital cardiac arrest (OHCA). …”
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Machine Learning Techniques for Pharmaceutical Bioinformatics
Published 2018“…In this matrix, each drug is represented by a vector of attributes from all other drugs. A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. …”
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186
The role of Reinforcement Learning in software testing
Published 2023“…However, a systematic overview of the state-of-the-art on the role of reinforcement learning in software testing is lacking.…”
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A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
Published 2025“…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”
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190
Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey
Published 2024“…As new <u>malware</u> gets introduced frequently by <u>malware developers</u>, it is very challenging to come up with comprehensive algorithms to detect this malware. There are many machine-learning and deep-learning algorithms have been developed by researchers. …”
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191
A comparative analysis to forecast carbon dioxide emissions
Published 2022“…After evaluating those deep learning models, a multivariate polynomial regression has also been employed to forecast CO<sub>2 </sub>emissions. …”
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192
NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY
Published 2022“…Therefore, this thesis proposed a Novel Stacking Classification and Prediction (NSCP) algorithm based on AAL for the older people with Multi-strategy Combination based Feature Selection (MCFS) and Novel Clustering Aggregation (NCA) algorithms. …”
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193
Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
Published 2023“…Additionally, the machine learning algorithms are classified as either supervised or unsupervised, and they are further partitioned if the amount of work that falls under a certain scheme is significant. …”
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194
Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 2025“…Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”
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195
Using artificial intelligence to improve body iron quantification: A scoping review
Published 2023“…The search revealed a wide range of machine learning algorithms used by different studies. …”
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Random vector functional link network: Recent developments, applications, and future directions
Published 2023“…Finally, we present potential future research directions/opportunities that can inspire the researchers to improve the RVFL’s architecture and learning algorithm further. </p> <h2>Other Information</h2> <p>Published in: Applied Soft Computing<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/ </a> <br> See article on publisher's website: <a href="http://dx.doi.org/10.1016/j.asoc.2023.110377" target="_blank">http://dx.doi.org/10.1016/j.asoc.2023.110377</a> </p>…”
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198
Robustness and Convergence of P-type Learning Control
Published 1993“…The robustness and convergence of P-type learning control algorithms for a class of time-varying, nonlinear systems to state disturbances, measurement noise at the output, and reinitialization errors at each iteration is studied extensively. …”
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199
Identification of phantom movements with an ensemble learning approach
Published 2022“…In the current study, we utilized ensemble learning algorithms for the recognition and classification of phantom movements of the different amputation levels of the upper and lower extremity. …”
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200