Towards Improving Modeling and Simulation of Clinical Pathways: Lessons Learned and Future Insights. - Mahmoud Elbattah; Owen Molloy (SIMULTECH, 2015)

Using Machine Learning to Predict Length of Stay and Discharge Destination for Hip-Fracture Patients. - Mahmoud Elbattah; Owen Molloy (IntelliSys (1), 2016)

Coupling Simulation with Machine Learning: A Hybrid Approach for Elderly Discharge Planning. - Mahmoud Elbattah; Owen Molloy (SIGSIM-PADS, 2016)

Clustering-Aided Approach for Predicting Patient Outcomes with Application to Elderly Healthcare in Ireland. - Mahmoud Elbattah; Owen Molloy (AAAI Workshops, 2017)

Data-driven patient segmentation using K-means clustering: the case of hip fracture care in Ireland. - Mahmoud Elbattah; Owen Molloy (ACSW, 2017)

Learning about systems using machine learning: Towards more data-driven feedback loops. - Mahmoud Elbattah; Owen Molloy (WSC, 2017)

ScholarBase: Towards a Cross-Domain Knowledgebase for Linked Scholarly Data. - Mahmoud Elbattah (SWM@WSDM, 2017)

Visualization of Eye-Tracking Patterns in Autism Spectrum Disorder: Method and Dataset. - Romuald Carette; Mahmoud Elbattah; Gilles Dequen; Jean-Luc Guérin; Federica Cilia (ICDIM, 2018)

ML-Aided Simulation: A Conceptual Framework for Integrating Simulation Models with Machine Learning. - Mahmoud Elbattah; Owen Molloy (SIGSIM-PADS, 2018)

Designing Care pathways using simulation Modeling and Machine Learning. - Mahmoud Elbattah; Owen Molloy; Bernard P. Zeigler (WSC, 2018)

Learning to Predict Autism Spectrum Disorder based on the Visual Patterns of Eye-tracking Scanpaths. - Romuald Carette; Mahmoud Elbattah; Federica Cilia; Gilles Dequen; Jean-Luc Guérin; Jérôme Bosche (HEALTHINF, 2019)

How can Machine Learning Support the Practice of Modeling and Simulation? - A Review and Directions for Future Research. - Mahmoud Elbattah (DS-RT, 2019)

Learning Clusters in Autism Spectrum Disorder: Image-Based Clustering of Eye-Tracking Scanpaths with Deep Autoencoder. - Mahmoud Elbattah; Romuald Carette; Gilles Dequen; Jean-Luc Guérin; Federica Cilia (EMBC, 2019)

Learning Triple Sequence Patterns in Knowledge Graphs to Predict Inconsistencies. - Mahmoud Elbattah; Conor Ryan (KMIS, 2019)

Deep Learning to Predict Hospitalization at Triage: Integration of Structured Data and Unstructured Text. - Émilien Arnaud; Mahmoud Elbattah; Maxime Gignon; Gilles Dequen (IEEE BigData, 2020)

Multi-channel ConvNet Approach to Predict the Risk of in-Hospital Mortality for ICU Patients. - Fabien Viton; Mahmoud Elbattah; Jean-Luc Guérin; Gilles Dequen (DeLTA, 2020)

Heatmaps for Visual Explainability of CNN-Based Predictions for Multivariate Time Series with Application to Healthcare. - Fabien Viton; Mahmoud Elbattah; Jean-Luc Guérin; Gilles Dequen (ICHI, 2020)

Generative Modeling of Synthetic Eye-tracking Data: NLP-based Approach with Recurrent Neural Networks. - Mahmoud Elbattah; Jean-Luc Guérin; Romuald Carette; Federica Cilia; Gilles Dequen (IJCCI, 2020)

NLP-Based Approach to Detect Autism Spectrum Disorder in Saccadic Eye Movement. - Mahmoud Elbattah; Jean-Luc Guérin; Romuald Carette; Federica Cilia; Gilles Dequen (SSCI, 2020)

The Role of Text Analytics in Healthcare: A Review of Recent Developments and Applications. - Mahmoud Elbattah; Émilien Arnaud; Maxime Gignon; Gilles Dequen (HEALTHINF, 2021)

NLP-Based Prediction of Medical Specialties at Hospital Admission Using Triage Notes. - Émilien Arnaud; Mahmoud Elbattah; Maxime Gignon; Gilles Dequen (ICHI, 2021)

Variational Autoencoder for Image-Based Augmentation of Eye-Tracking Data. - Mahmoud Elbattah; Colm Loughnane; Jean-Luc Guérin; Romuald Carette; Federica Cilia; Gilles Dequen (J. Imaging, 2021)

Learning Embeddings from Free-text Triage Notes using Pretrained Transformer Models. - Émilien Arnaud; Mahmoud Elbattah; Maxime Gignon; Gilles Dequen (HEALTHINF, 2022)

Vision-based Approach for Autism Diagnosis using Transfer Learning and Eye-tracking. - Mahmoud Elbattah; Jean-Luc Guérin; Romuald Carette; Federica Cilia; Gilles Dequen (HEALTHINF, 2022)

Explainable NLP Model for Predicting Patient Admissions at Emergency Department Using Triage Notes. - Émilien Arnaud; Mahmoud Elbattah; Pedro A. Moreno-Sánchez; Gilles Dequen; Daniel Aiham Ghazali (IEEE Big Data, 2023)

Predictive models in emergency medicine and their missing data strategies: a systematic review. - Émilien Arnaud; Mahmoud Elbattah; Christine Ammirati; Gilles Dequen; Daniel Aiham Ghazali (npj Digit. Medicine, 2023)

Exploring the Ethical Challenges of Large Language Models in Emergency Medicine: A Comparative International Review. - Mahmoud Elbattah; Émilien Arnaud; Daniel Aiham Ghazali; Gilles Dequen (BIBM, 2024)

Consistency of XAI Models against Medical Expertise: An Assessment Protocol. - Émilien Arnaud; Mahmoud Elbattah; Amandine Pitteman; Gilles Dequen; Daniel Aiham Ghazali; Pedro A. Moreno-Sánchez (ICHI, 2024)

Editorial: Improving autism spectrum disorder diagnosis using machine learning techniques. - Mahmoud Elbattah; Osman Ali Sadek Ibrahim; Gilles Dequen (Frontiers Neuroinformatics, 2024)