Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. Experimental results demonstrated that DL algorithms leveraging sampling methods perform significantly worse than the decision tree-based ensemble method. …”

Gene-specific machine learning model to predict the pathogenicity of BRCA2 variants by Mohannad N. Khandakji (13885434)

“…The model utilizes general variant information such as position, frequency, and consequence for the canonical BRCA2 transcript, as well as deleteriousness prediction scores from several tools. We trained the model on 80% of the expert reviewed variants by the Evidence-Based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium and tested its performance on the remaining 20%, as well as on an independent set of variants of uncertain significance with experimentally determined functional scores.…”

Enhancing the Prediction of Breast Cancer Progression Through Multi-modal Data Transformation by Faseela Abdullakutty (22564814)

“…A comparison was conducted between three prediction approaches: a unimodal approach, an early fusion approach based on concatenation, and the Multi Co-Guided Attention (MCGA) approach. …”

A Comprehensive Review on Membrane Fouling: Mathematical Modelling, Prediction, Diagnosis, and Mitigation by AlSawaftah, Nour Majdi

“…Membrane-based separation has gained increased popularity over the past few decades, particularly reverse osmosis (RO). …”
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Optimal management, prevalence, and clinical behavior of saddle pulmonary embolism: A systematic review and meta-analysis by Fateen Ata (12217764)

“…<h3>Introduction</h3><p dir="ltr">The central location, size, and instability of saddle pulmonary embolism (SPE) have raised significant concerns regarding its clinical, hemodynamic effects as well as optimal management. …”

B5G: Predictive Container Auto-Scaling for Cellular Evolved Packet Core by Yahuza Bello (19645930)

“…Our findings show the superiority of container-based model over VM-based model in terms of resource utilization. …”

AN EXAMINATION OF THE PREDICTIVE FACTORS ON STUDENTS' MOTIVATION FOR SUCCESS IN UNDERGRADUATE INTRODUCTORY MATHEMATICS COURSES IN THE UAE by HAMMOUDI, MOHAMAD MUSTAFA

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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning by Zeinab, Samira Jihad

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Can the Salivary Microbiome Predict Cardiovascular Diseases? Lessons Learned From the Qatari Population by Selvasankar Murugesan (4376506)

“…This is the first study to apply ML-based prediction modeling using the SM to predict CVD in an Arab population. …”

Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression by Alaa Abd-Alrazaq (17430900)

“…Until further research improve its performance, wearable AI should be used in conjunction with other methods for diagnosing and predicting depression. Further studies are needed to examine the performance of wearable AI based on a combination of wearable device data and neuroimaging data and to distinguish patients with depression from those with other diseases.…”

Effectiveness of Positron Emission Tomography for Predicting Chemotherapy Response in Colorectal Cancer Liver Metastases by Glazer, Evan

“…When performed within 4 weeks of chemotherapy, PET had a negative predictive value of 13.3% and a positive predictive value of 94.3%. …”
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Using Data Mining and Text Mining Techniques in Predicting the Price of Real Estate Properties in Dubai by Khashan, Deena Younis Abo

“…The results of linear regression predictions based on the structured features are considered as the baseline of the research. …”
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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

“…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …”

Epigenetic analysis of Paget’s disease of bone identifies differentially methylated loci that predict disease status by Ilhame Diboun (3522413)

“…Meta-analysis of data from the discovery and cross-validation set, each comprising 116 PDB cases and 130 controls, revealed significant differences in DNA methylation at 14 CpG sites, 4 CpG islands, and 6 gene-body regions. …”

Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…The removal efficiencies in the proposed ENR-BP were four fold higher than the suspended growth process and in the same order of magnitude of 5-stage Bardenpho-MBBR. The developed ANN-based model provides an efficient and robust tool for predicting and forecasting the performance of the ENR-BP.…”

Accurate prediction of dynamic viscosity of polyalpha-olefin boron nitride nanofluids using machine learning by Ahmad K. Sleiti (15955149)

“…These results suggest that the use of machine learning models can significantly improve the accuracy of predicting the viscosity of PAO-hBN nanofluids. …”

Nutritional Status and Clinical Outcomes of Children with Medical Complexity in the United Arab Emirates: A Retrospective Cross-Sectional Study by Al Slaybe, Maryam

“…Although undernourished children exhibited higher rates of early readmission, recurrent admission, and in-hospital mortality, these associations were not statistically significant. Conclusion: Undernutrition is alarmingly high among hospitalized CMCs, with a significant association with adverse clinical outcomes, including prolonged hospitalization. …”
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A customised fetal growth and birthweight standard for Qatar: a population-based cohort study by Thomas Farrell (3933833)

“…</p><h3>Methods</h3><p dir="ltr">The PEARL registry data on women delivering in Qatar (2017–2018) was used to develop a multivariable linear regression model predicting optimal birthweight. …”

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

“…Ensemble method is a tool that merges several base models in order to produce one optimal predictive model. …”

Biochar yield prediction using response surface methodology: effect of fixed carbon and pyrolysis operating conditions by Sabah Mariyam (14150859)

“…An empirical equation is developed based on a statistically significant quadratic model to produce optimized biochar yield with high prediction accuracy. …”