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201
Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…We present a comprehensive analysis of the various fusion strategies, the diseases and clinical outcomes for which multimodal fusion was used, the ML algorithms used to perform multimodal fusion for each clinical application, and the available multimodal medical datasets. …”
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202
The role of Reinforcement Learning in software testing
Published 2023“…</p><h3>Results</h3><p dir="ltr">This study highlights different software testing types to which RL has been applied, commonly used RL algorithms and architecture for learning, challenges faced, advantages and disadvantages of using RL, and the performance comparison of RL-based models against other techniques.…”
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203
Data mining approach to predict student's selection of program majors
Published 2019“…Naïve Bayes, Decision Trees offered the best predictions across the different sampling techniques. This study presents an approach to design and deploy a data mining project that can be used as a basis for developing systems to enable the selection of student majors.…”
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204
Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier
Published 2021“…This study focuses on the future prediction of the effectiveness of the COVID-19 vaccine effectiveness which has been presented as a light in the dark. …”
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205
Current trends and future orientation in diagnosing lung pathologies: A systematic survey
Published 2025“…The study underscored the potential of these techniques to enhance the diagnosis of lung pathologies and VAP and presents the advances in the field of smart biomedical applications. …”
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206
Machine Learning Techniques for Pharmaceutical Bioinformatics
Published 2018“…A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. This dissertation presents a case study of predicted anti-cancer activity for 38 drugs. …”
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207
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208
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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209
A Systematic Literature Review on Phishing Email Detection Using Natural Language Processing Techniques
Published 2022“…Based on specific predefined criteria, a total of 100 research articles published between 2006 and 2022 were identified and analysed. We study the key research areas in phishing email detection using NLP, machine learning algorithms used in phishing detection email, text features in phishing emails, datasets and resources that have been used in phishing emails, and the evaluation criteria. …”
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210
Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan
Published 2017“…Different classification algorithms were applied to the dataset using the Rapidminer tool. …”
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211
Building power consumption datasets: Survey, taxonomy and future directions
Published 2020“…Based on the analytical study, a novel dataset has been presented, namely Qatar university dataset, which is an annotated power consumption anomaly detection dataset. …”
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212
LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications
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213
BioNetApp: An interactive visual data analysis platform for molecular expressions
Published 2019“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.</p><h3>Conclusion</h3><p dir="ltr">BioNetApp has been utilized in a metabolomics study to investigate the metabolite abundance changes in alcohol induced fatty liver, where pair-wise analyses of metabolome concentration revealed correlation networks and interesting patterns in the metabolomics dataset. …”
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214
Validating a new model for rapid multi-dimensional combined heat and air infiltration building energy simulation
Published 2015“…The study found that even the most advanced current algorithms have up to 96.13% relative error versus CFD analysis. …”
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215
The Impact of AI on Decision-Making in Educational Management: Benefits, Risks, and Ethical Concerns
Published 2024“…However, the adoption of AI also presents challenges, including potential biases in algorithms, privacy concerns, and the risk of an over-reliance on automated systems. …”
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216
Correlation Clustering via 2-Club Clustering with Vertex Splitting
Published 2024“…Both of these problems are proved to be NP-Hard and heuristics are presented for 2CCED and 2CCEDVS.We compare the heuristic’s performance against well-known clustering algorithms on Biological and Social Networks. …”
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217
Decision-level Gait Fusion for Human Identification at a Distance
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doctoralThesis -
218
Stacking-based ensemble learning for remaining useful life estimation
Published 2023“…Therefore, predictive maintenance models are developed to estimate the right time for maintenance. In this study, predictive models that estimate the remaining useful life of turbofan engines have been developed using deep learning algorithms on NASA’s turbofan engine degradation simulation dataset. …”
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219
An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
Published 2022“…Therefore, it is imperative to account for these adverse effects of the integration of DERs on the distribution network and minimize their impact when calculating the Hosting Capacity (HC). Two algorithms are presented in this study derived from a novel modified iterative method and a novel Repeated Particle Swarm Optimization (RPSO) method for determining the HC for multiple DER units simultaneously or a single DER unit integrating into radial or mesh networks. …”
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220
An aspect-oriented framework for systematic security hardening of software
Published 2008“…We also explore the viability of the proposed pointcuts and primitives by elaborating and implementing their algorithms and presenting the result of explanatory case studies. …”
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masterThesis