KNNOR: An oversampling technique for imbalanced datasets by Ashhadul Islam (16869981)

“…To overcome these problems, this article proposes an advanced algorithm by studying the compactness and location of the minority class relative to other classes. …”

Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia by Hanan Ehtewish (17149825)

“…There was also the dysregulation of 153 plasma proteins in individuals with dementia compared with those with MCI, and machine learning algorithms identified 8 biomarkers that classified dementia from MCI with an AUC of 0.87 ± 0.07. …”

Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter by Mena S. ElMenshawy (17983807)

“…Matlab/Simulink platform is used to apply the AEKF and FFAEKF algorithms on the load dataset. Results have demonstrated that the FFAEKF improves the forecasting performance through providing less MaxAE and less RMSE. …”

Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection by Ahmad Yaser Alhaddad (7017434)

“…Convolutional and recurrent neural networks, support vector machines, and decision trees are examples of such machine learning algorithms. Finally, we address the key limitations and challenges of these studies and provide recommendations for future work.…”

Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis by Jithin Kalathikudiyil Sreedharan (18268894)

“…It uses various models and algorithms to detect patterns and specific findings to diagnose a disease with utmost accuracy. …”

New aspect-oriented constructs for security hardening concerns by Mourad, Azzam

“…We find these pointcuts and primitives to be necessary because they are needed to perform many security hardening practices and, to the best of our knowledge, none of the existing ones can provide their functionalities. Moreover, we show the viability and correctness of the proposed pointcuts and primitives by elaborating and implementing their algorithms and presenting the result of explanatory case studies.…”
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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review by Zainab Jan (17306614)

“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”

Dynamic Cyber Resilience of Interdependent Critical Information Infrastructures by JUMA, MAZEN GHAZI

“…The technology stack was also enhanced with three new algorithms and five protocols. The proposed solution was optimized using the iterative four-objective cycle based on previous primary phase results. …”
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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…</p><h3>Research Design & Methods</h3><p dir="ltr">The study aimed to investigate performance of AI models in estimating BGL among diabetic patients using non-invasive wearable devices data An open-source dataset was used which provided BGL readings, diabetic status (Diabetic or non-diabetic), heart rate, Blood oxygen level (SPO2), Diastolic Blood pressure, Systolic Blood Pressure, Body temperature, Sweating, and Shivering for 13 participants by age group taken from WDs. …”

Nouveaux points de coupure et primitives pour les préoccupations de renforcement de sécurité by Mourad, Azzam

“…We find these pointcuts and primitives to be necessary because they are needed to perform many security hardening practices and, to the best of our knowledge, none of the existing ones can provide their functionalities. Moreover, we show the viability and correctness of our proposed pointcuts and primitives by elaborating and implementing their algorithms and presenting the results of explanatory case studies.…”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques by Sjoerd Boeschoten (17347045)

“…This framework can generate different machine learning models, which provide comparable results compared to other studies. …”

Optimal Dispatch of Mobile Energy Storage Unit to Support EV Charging Stations by Elmeligy, Mohamed Mostafa Abdelazim

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The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs by Muhammad Kashif (3923483)

“…One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …”

Artificial intelligence-based methods for fusion of electronic health records and imaging data by Farida Mohsen (16994682)

“…Multimodal data used in the included studies were mostly from private repositories (21 studies). …”

Assessment and Performance Analysis of Machine Learning Techniques for Gas Sensing E-nose Systems by Mahmood, Lubna Syeda

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Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic by Saeed Al-Maroof, Rana

“…The data obtained from the study were analyzed by using the partial least squares structural equation modeling (PLS-SEM) and machine learning algorithms. …”
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Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Modern ML models are used for prediction, prioritization, and decision making. Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations by Mueen Uddin (4903510)

“…Besides this, we have discussed the GAI limitations, such as occasional incorrect results, expensive training, and the potential for misuse by malicious actors for illegal activities. This research study also provides valuable insights into the balanced adoption of GAI in cybersecurity, ensuring effective threat migration without compromising system integrity.…”

A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity by Abdullah Al Siam (22304047)

“…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. …”

Urinary Metabolomic Markers of Protein Glycation, Oxidation, and Nitration in Early-Stage Decline in Metabolic, Vascular, and Renal Health by Jinit Masania (7164239)

“…Machine learning was applied to optimise and validate algorithms to discriminate between study groups for potential diagnostic utility. …”