Predicting Dropouts among a Homogeneous Population using a Data Mining Approach by BILQUISE, GHAZALA

“…Our study also reveals that ensemble machine learning algorithms are more reliable and outperform standard algorithms.…”
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An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network by Tawfik Beghriche (19563184)

“…A performance comparison between the DNN algorithm and some well‐known machine learning techniques as well as the state‐of‐the‐art methods is presented. …”

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

“…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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Competitive learning/reflected residual vector quantization for coding angiogram images by Mourn, W.A.H.

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A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

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Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties by AbdulGhafour, Husaen

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

ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification by Md. Iqbal Hossain (723299)

Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn... by Mohamed, AlShuweihi

“…Machine Learning (ML) saw a great increase in general and domain specific research. …”
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Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm by Khadija Attouri (18024307)

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

“…We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). Limma-based differential expression analysis reported the dysregulation of 61 proteins in the plasma of those with dementia compared with controls, and machine learning algorithms identified 17 stable diagnostic biomarkers that differentiated individuals with AUC = 0.98 ± 0.02. …”

Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice by Turker Tuncer (16677966)

“…Our approach is a simple and efficient voice-based algorithm in which a multi-center and multi threshold based ternary pattern is used (MCMTTP). …”

Development of a deep learning-based group contribution framework for targeted design of ionic liquids by Sadah Mohammed (18192859)

Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…For such high-dimension data our approach outperforms the Synthetic Minority Oversampling Technique for Regression (SMOTER) algorithm for the IMDB-WIKI and AgeDB image datasets. …”

Dynamic adaptation for video streaming over mobile devices. (c2013) by Jalloul, Rayan A.

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A machine learning approach for localization in cellular environments by Abdallah, Ali A.

“…A machine learning approach is developed for localization based on received signal strength (RSS) from cellular towers. …”
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LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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Reinforcement Learning-Based School Energy Management System by Yassine Chemingui (18891757)

Artificial intelligence based anomaly detection of energy consumption in buildings: A review, current trends and new perspectives by Yassine Himeur (14158821)

“…In this regard, this paper is an in-depth review of existing anomaly detection frameworks for building energy consumption based on artificial intelligence. Specifically, an extensive survey is presented, in which a comprehensive taxonomy is introduced to classify existing algorithms based on different modules and parameters adopted, such as machine learning algorithms, feature extraction approaches, anomaly detection levels, computing platforms and application scenarios. …”