Estimation of Travel Time in the City Based on Intelligent Transportation System Traffic Data with the Use of Neural Networks. - Piotr Ciskowski; Adrianna Janik; Marek Bazan; Krzysztof Halawa; Tomasz Janiczek; Andrzej Rusiecki (DepCoS-RELCOMEX, 2016)

Interpreting Black-Box Semantic Segmentation Models in Remote Sensing Applications. - Adrianna Janik; Kris Sankaran; Anthony Ortiz (MLVis@EuroVis, 2019)

On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer. - Sameh K. Mohamed; Brian Walsh; Mohan Timilsina; Vít Novácek; Maria Torrente; Fabio Franco; Mariano Provencio; Adrianna Janik; Luca Costabello; Pontus Stenetorp; Pasquale Minervini (AMIA, 2021)

Interpretability of a deep learning model in the application of cardiac MRI segmentation with an ACDC challenge dataset. - Adrianna Janik; Jonathan Dodd; Georgiana Ifrim; Kris Sankaran; Kathleen M. Curran (Image Processing, 2021)

Integration of Clinical Information and Imputed Aneuploidy Scores to Enhance Relapse Prediction in Early Stage Lung Cancer Patients. - Mohan Timilsina; Samuele Bousi; Dirk Fey; Adrianna Janik; Maria Torrente; Mariano Provencio; Alberto Bermúdez; Enric Carcereny; Luca Costabello; Delvys Rodriguez Abreu; Manuel Cobo; Rafael Castro; et al. (AMIA, 2022)

Unsupervised Customer Segmentation with Knowledge Graph Embeddings. - Sumit Pai; Fiona Brennan; Adrianna Janik; Teutly Correia; Luca Costabello (WWW (Companion Volume), 2022)

Discovering Concepts in Learned Representations using Statistical Inference and Interactive Visualization. - Adrianna Janik; Kris Sankaran (CoRR, 2022)

Sampling Strategy for Fine-Tuning Segmentation Models to Crisis Area under Scarcity of Data. - Adrianna Janik; Kris Sankaran (CoRR, 2022)

Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients. - Adrianna Janik; Maria Torrente; Luca Costabello; Virginia Calvo; Brian Walsh; Carlos Camps; Sameh K. Mohamed; Ana L. Ortega; Vít Novácek; Bartomeu Massutí; Pasquale Minervini; M. Rosario Garcia Campelo; et al. (CoRR, 2022)

Explaining Link Predictions in Knowledge Graph Embedding Models with Influential Examples. - Adrianna Janik; Luca Costabello (CoRR, 2022)

Machine Learning Survival Models for Relapse Prediction in a Early Stage Lung Cancer Patient. - Mohan Timilsina; Samuele Buosi; Adrianna Janik; Pasquale Minervini; Luca Costabello; Maria Torrente; Mariano Provencio; Virginia Calvo; Carlos Camps; Ana L. Ortega; Bartomeu Massutí; M. Rosario Garcia Campelo; et al. (IJCNN, 2023)

Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer. - Mohan Timilsina; Dirk Fey; Samuele Buosi; Adrianna Janik; Luca Costabello; Enric Carcereny; Delvys Rodriguez Abreu; Manuel Cobo; Rafael Castro; Reyes Bernabé; Pasquale Minervini; Maria Torrente; et al. (J. Biomed. Informatics, 2023)

Certificates of Differential Privacy and Unlearning for Gradient-Based Training. - Matthew Wicker; Philip Sosnin; Adrianna Janik; Mark N. Müller; Adrian Weller; Calvin Tsay (CoRR, 2024)

Machine learning estimated probability of relapse in early-stage non-small-cell lung cancer patients with aneuploidy imputation scores and knowledge graph embeddings. - Samuele Buosi; Mohan Timilsina; Adrianna Janik; Luca Costabello; Maria Torrente; Mariano Provencio; Dirk Fey; Vít Novácek (Expert Syst. Appl., 2024)