Robert Keight

Liverpool John Moores University — United Kingdom

Computer Science · Physical Sciences

13h-index623citations18works0.02yr avg
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Research Topics

Imbalanced Data Classification Techniques(7), Online Learning and Analytics(5), Hemoglobinopathies and Related Disorders(4), Topic Modeling(2), Migraine and Headache Studies(2)

Publications18 total

Students Performance Prediction in Online Courses Using Machine Learning Algorithms
2020· 71 citedOpen Access
Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques
IEEE Access·2019· 64 citedOpen Access
Predicting Freezing of Gait in Parkinsons Disease Patients Using Machine Learning
2018· 37 cited
A Data Science Methodology Based on Machine Learning Algorithms for Flood Severity Prediction
2018· 46 citedOpen Access
The Application of Gaussian Mixture Models for the Identification of At-Risk Learners in Massive Open Online Courses
2018· 32 citedOpen Access
Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach
IEEE Access·2018· 54 citedOpen Access
Big Data and Data Science Applications for Independent and Healthy Living
2017· 4 cited
Recurrent Neural Network Architectures for Analysing Biomedical Data Sets
2017· 24 cited
Machine learning approaches to predict learning outcomes in Massive open online courses
2017· 117 cited
Towards the discrimination of primary and secondary headache: An intelligent systems approach
2017· 10 cited
An Intelligent Systems Approach to Primary Headache Diagnosis
Lecture notes in computer science·2017· 21 cited
Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses
Lecture notes in computer science·2017· 13 citedOpen Access
A Performance Evaluation of Systematic Analysis for Combining Multi-class Models for Sickle Cell Disorder Data Sets
Lecture notes in computer science·2017· 4 cited
Machine learning approaches to the application of disease modifying therapy for sickle cell using classification models
Neurocomputing·2016· 53 citedOpen Access
The utilisation of composite machine learning models for the classification of medical datasets for sickle cell disease
2016· 17 cited
Training Neural Networks as Experimental Models: Classifying Biomedical Datasets for Sickle Cell Disease
Lecture notes in computer science·2016· 13 citedOpen Access
Applied Difference Techniques of Machine Learning Algorithm and Web-Based Management System for Sickle Cell Disease
2015· 7 cited
Artificial Intelligence for Detecting Preterm Uterine Activity in Gynecology and Obstetric Care
2015· 36 citedOpen Access

Frequent Co-authors

Abir Hussain(14), Dhiya Al‐Jumeily(10), Paul Fergus(9), Mohammed Khalaf(8), Raghad Al-Shabandar(6), Russell Keenan(6), Ibrahim Olatunji Idowu(6), Abir Hussain(4), Andy Laws(3), Janet Lunn(2), Panos Liatsis(2), Thar Baker(2), Ala S. Al Kafri(2), Haya Alaskar(2), Carl Chalmers(2), Conor Mallucci(2), Naeem Radi(1), Wasiq Khan(1), Posco Tso(1), Paulo Lisböa(1)