Using Case-Based Reasoning to Predict Marathon Performance and Recommend Tailored Training Plans. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (ICCBR, 2020)

Providing Explainable Race-Time Predictions and Training Plan Recommendations to Marathon Runners. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (RecSys, 2020)

A Case-Based Reasoning Approach to Predicting and Explaining Running Related Injuries. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (ICCBR, 2021)

Using Machine Learning Techniques to Support Marathon Runners. - Ciara Feely (ICCBR Doctoral Consortium, 2022)

An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (ICCBR, 2022)

Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners. - Barry Smyth; Aonghus Lawlor; Jakim Berndsen; Ciara Feely (User Model. User Adapt. Interact., 2022)

Modelling the Training Practices of Recreational Marathon Runners to Make Personalised Training Recommendations. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (UMAP, 2023)

A Case-Based Reasoning Approach to Post-injury Training Recommendations for Marathon Runners. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (ICCBR, 2024)

Recommending Personalised Targeted Training Adjustments for Marathon Runners. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (RecSys, 2024)

Using Pseudo Cases and Stratified Case-Based Reasoning to Generate and Evaluate Training Adjustments for Marathon Runners. - Ciara Feely; Brian Caulfield 001; Aonghus Lawlor; Barry Smyth (SGAI Conf. (2), 2024)