Mining Adverse Drug Events Using Multiple Feature Hierarchies and Patient History Windows. - Maria Bampa; Panagiotis Papapetrou (ICDM Workshops, 2019)

Handling temporality of clinical events with application to Adverse Drug Event detection in Electronic Health Records: A scoping review. - Maria Bampa (CoRR, 2019)

Aggregate-Eliminate-Predict: Detecting Adverse Drug Events from Heterogeneous Electronic Health Records. - Maria Bampa; Panagiotis Papapetrou (CoRR, 2019)

A Clustering Framework for Patient Phenotyping with Application to Adverse Drug Events. - Maria Bampa; Panagiotis Papapetrou; Jaakko Hollmén (CBMS, 2020)

Detecting Adverse Drug Events from Swedish Electronic Health Records using Text Mining. - Maria Bampa; Hercules Dalianis (MultiligualBIO@LREC, 2020)

EpidRLearn: Learning Intervention Strategies for Epidemics with Reinforcement Learning. - Maria Bampa; Tobias Fasth; Sindri Magnússon; Panagiotis Papapetrou (AIME, 2022)

A Workflow for Generating Patient Counterfactuals in Lung Transplant Recipients. - Franco Rugolon; Maria Bampa; Panagiotis Papapetrou (PKDD/ECML Workshops (2), 2022)

A Workflow for Creating Multimodal Machine Learning Models for Metastasis Predictions in Melanoma Patients. - Franco Rugolon; Korbinian Randl; Maria Bampa; Panagiotis Papapetrou (PKDD/ECML Workshops (4), 2023)

M-ClustEHR: A multimodal clustering approach for electronic health records. - Maria Bampa; Ioanna Miliou; Braslav Jovanovic; Panagiotis Papapetrou (Artif. Intell. Medicine, 2024)

Data-Driven AI for Patient and Public Health: On the Use of Multisource and Multimodal Data in Machine Learning to Improve Healthcare - Maria Bampa (2024)