Predictive modelling in times of public health emergencies: patients’ non-transport decisions during the COVID-19 pandemic by Hassan Farhat (9000509)

“…</p><h3>Conclusion</h3><p dir="ltr">This study indicated that predictive modelling could accurately help identify patients who refuse transport to hospital and may not require treatment on the scene. …”

Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniques by Umesh Kumar Lilhore (17727684)

“…This research proposed an efficient feature selection and prediction model for cervical cancer datasets using Boruta analysis and SVM method to deal with this challenge. …”

Closed-form Exact and Asymptotic Expressions for the Symbol Error Rate and Channel Capacity of the H-function Fading Channel by Alhennawi, Husam R.

“…The derived exact expressions are given in terms of the univariate and multivariate Fox H functions for which we provide a portable and efficient Python code. Since the Fox's H-function fading channel represents the most generalized fading model ever presented in the literature, the derived expressions subsume most of those previously presented for all the known simple and composite fading models. …”
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Arabic Educational Neural Network Chatbot by A. Alazzam, Bayan

“…Finally, we programmed the chabot and the models in Python. As a consequence, an Arabic chatbot answers all questions about educational regulations in the United Arab Emirates.…”
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A study on Speaker Recognition System by Bakkar, Hazem Wa'il Mohammed

“…Another main goal for conducting this research is to make a scientific comparison between tools and methods that are related to speaker recognition domain, the following are the techniques that were studied : 1) Energy based tool and Long-Term Spectral Divergence (LTSD) in the preprocessing module of the system, 2) Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictive Cepstral Coefficients (LPCC) in the feature extraction module, and 3) scikit-learn Gaussian Mixture Model (GMM), Universal Background Model (UBM), Continuous Restricted Boltzmann Machine (CRBM) and Joint Factor Analysis (JFA) in the recognition module. …”
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Investigation of Forming a Framework to shortlist contractors in the tendering phase by DABASH, MOHANNAD SALAH

“…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …”
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A Novel Bayesian Outlier Score Based on the Negative Binomial Distribution for Detecting Aberrantly Expressed Genes in RNA-Seq Gene Expression Count Data by Edin Salkovic (16891479)

“…The novel Bayesian model on which our score is based - OutPyRX (Outlier detection in Python for RNA-Seq, eXtended version) - improves the model of its predecessor OutPyR by introducing novel parameters that are derived from OutPyR's. …”

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

“…<p>Predictive performance of Machine Learning (ML) models rely on the quality of data used for training the models. …”