Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review by Zainab Jan (17306614)

“…Most of the included articles used data sets with a size of <1000 samples (11/30, 37%). Deep learning models were the most prominent branch of AI used for pancreatic cancer diagnosis in the studies, and the convolutional neural network was the most used algorithm (18/30, 60%). …”

Artificial intelligence models for predicting the mode of delivery in maternal care by Rawan AlSaad (14159019)

“…The dataset included 12,639 vaginal deliveries and 4012 unplanned cesarean deliveries, with 92 variables recorded for each patient. Five machine learning algorithms were evaluated: XGBoost, AdaBoost, random forest, decision tree, and multi-layer perceptron (MLP) classifier. …”

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

A Parallel Algorithm for Inverse Halftoning and its Hardware Implementation by Siddiqi, Umair F.

“…Keywords: (1) Inverse Halftoning (2) Hardware Implementation (3) Look-Up Table Inverse Halftoning (4) Complex Programmable Logic Devices (CPLD) (5) Image Processing…”
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Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

Animal migration optimization algorithm: novel optimizer, analysis, and applications by Abualigah, Laith

“…It is based on the animal actions and habits in migration seasons. Optimization algorithms are applied to find the optimal solutions in many domains and fields such as image processing, machine learning, and others. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects by Mohamed Massaoudi (16888710)

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

“…Recently, deep learning models have achieved state-of-the-art performance for many healthcare prediction tasks. …”

Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid (22047578)

“…These processes begin with capturing speech in analog form and applying signal processing algorithms to ensure compatibility with devices like cochlear implants (CIs). …”

A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method by Shahid Rahman (16904613)

“…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. …”

Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)

Artificial Intelligence and Machine Learning Applications in Sudden Cardiac Arrest Prediction and Management: A Comprehensive Review by Sarah Aqel (17787809)

“…<h3>Purpose of Review</h3><p dir="ltr">This literature review aims to provide a comprehensive overview of the recent advances in prediction models and the deployment of AI and ML in the prediction of cardiopulmonary resuscitation (CPR) success. …”

An enhanced k-means clustering algorithm for pattern discovery in healthcare data by Haraty, Ramzi A.

“…The huge amounts of data generated by media sensors in health monitoring systems, by medical diagnosis that produce media (audio, video, image, and text) content, and from health service providers are too complex and voluminous to be processed and analyzed by traditional methods. …”
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Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain by Farshad Rahimi Ghashghaei (20880995)

“…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. …”

Interval-Valued Reduced Ensemble Learning Based Fault Detection and Diagnosis Techniques for Uncertain Grid-Connected PV Systems by Khaled Dhibi (16891524)

Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review by Yosra Magdi Mekki (21673721)

“…Studies were included if they focused on the application of AI in US imaging for CTS diagnosis. Editorials, expert opinions, conference papers, dataset publications, and studies that did not have a clear clinical application of the AI algorithm were excluded.…”

Machine Learning Techniques for Pharmaceutical Bioinformatics by SULTAN, AHMED ATTA AHMED

“…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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The role of Reinforcement Learning in software testing by Amr Abo-eleneen (17032284)

“…</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.…”

RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems. by Sebastian Kruse (18595195)

“…Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel enumeration algebra. …”