Ibrahim Olatunji Idowu

Liverpool John Moores University — United Kingdom

Medicine · Health Sciences

9h-index307citations14works0.02yr avg
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Research Topics

Hemoglobinopathies and Related Disorders(5), Preterm Birth and Chorioamnionitis(5), Neonatal and fetal brain pathology(4), Infant Development and Preterm Care(3), Imbalanced Data Classification Techniques(3)

Publications14 total

Securing Things in the Healthcare Internet of Things
2019· 30 cited
Forensic Analysis of Wearable Devices: Fitbit, Garmin and HETP Watches
2019· 25 cited
Recurrent Neural Network Architectures for Analysing Biomedical Data Sets
2017· 24 cited
Classification Techniques Using EHG Signals for Detecting Preterm Births
Liverpool John Moores University·2017· 9 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
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
Advanced artificial neural network classification for detecting preterm births using EHG records
Neurocomputing·2015· 84 cited
Artificial Intelligence for Detecting Preterm Uterine Activity in Gynecology and Obstetric Care
2015· 36 citedOpen Access
Robust Approach for Medical Data Classification and Deploying Self-Care Management System for Sickle Cell Disease
2015· 9 cited
Advance flood detection and notification system based on sensor technology and machine learning algorithm
2015· 33 cited
Advance Artificial Neural Network Classification Techniques Using EHG for Detecting Preterm Births
2014· 13 citedOpen Access
Evaluation of Advanced Artificial Neural Network Classification and Feature Extraction Techniques for Detecting Preterm Births Using EHG Records
Lecture notes in computer science·2014· 3 citedOpen Access

Frequent Co-authors

Paul Fergus(11), Abir Hussain(10), Mohammed Khalaf(8), Dhiya Al‐Jumeily(7), Robert Keight(6), Russell Keenan(6), Chelsea Dobbins(4), Áine MacDermott(2), Carl Chalmers(2), Haya Alaskar(2), Raúl V. Casaña Eslava(1), Phillip Kendrick(1), Mal Ashall(1), Qi Shi(1), Stephen E. G. Lea(1), Farkhund Iqbal(1), Babar Shah(1), Wafaa Mahdi Salih(1), Dhafar Hamed(1), H. Askar(1)