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ORCIDAdrianna Janik
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2020 – today
- 2024
[j2]Samuele Buosi
, Mohan Timilsina, Adrianna Janik, Luca Costabello, Maria Torrente, Mariano Provencio, Dirk Fey, Vít Novácek:
Machine learning estimated probability of relapse in early-stage non-small-cell lung cancer patients with aneuploidy imputation scores and knowledge graph embeddings. Expert Syst. Appl. 235: 121127 (2024)- [i6]Matthew Wicker, Philip Sosnin, Adrianna Janik, Mark N. Müller, Adrian Weller, Calvin Tsay:
Certificates of Differential Privacy and Unlearning for Gradient-Based Training. CoRR abs/2406.13433 (2024) - 2023
- [j1]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, Mariano Provencio, Vít Novácek:
Synergy between imputed genetic pathway and clinical information for predicting recurrence in early stage non-small cell lung cancer. J. Biomed. Informatics 144: 104424 (2023) - [c7]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, Edel del Barco, Joaquim Bosch-Barrera, Vít Novácek:
Machine Learning Survival Models for Relapse Prediction in a Early Stage Lung Cancer Patient. IJCNN 2023: 1-8 - 2022
- [c6]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, Reyes Bernabé, Maria Guirado, Pasquale Minervini, Vít Novácek:
Integration of Clinical Information and Imputed Aneuploidy Scores to Enhance Relapse Prediction in Early Stage Lung Cancer Patients. AMIA 2022 - [c5]Sumit Pai, Fiona Brennan, Adrianna Janik, Teutly Correia, Luca Costabello:
Unsupervised Customer Segmentation with Knowledge Graph Embeddings. WWW (Companion Volume) 2022: 157-161 - [i5]Adrianna Janik, Kris Sankaran:
Discovering Concepts in Learned Representations using Statistical Inference and Interactive Visualization. CoRR abs/2202.04753 (2022) - [i4]Adrianna Janik, Kris Sankaran:
Sampling Strategy for Fine-Tuning Segmentation Models to Crisis Area under Scarcity of Data. CoRR abs/2202.04766 (2022) - [i3]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, Edel del Barco, Joaquim Bosch-Barrera, Ernestina Menasalvas, Mohan Timilsina, Mariano Provencio:
Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients. CoRR abs/2211.09856 (2022) - [i2]Adrianna Janik, Luca Costabello:
Explaining Link Predictions in Knowledge Graph Embedding Models with Influential Examples. CoRR abs/2212.02651 (2022) - 2021
- [c4]Sameh K. Mohamed, Brian Walsh, Mohan Timilsina, Vít Novácek, Maria Torrente, Fabio Franco, Mariano Provencio, Adrianna Janik, Luca Costabello, Pontus Stenetorp, Pasquale Minervini:
On Predicting Recurrence in Early Stage Non-small Cell Lung Cancer. AMIA 2021 - [c3]Adrianna Janik, Jonathan Dodd, Georgiana Ifrim, Kris Sankaran, Kathleen M. Curran:
Interpretability of a deep learning model in the application of cardiac MRI segmentation with an ACDC challenge dataset. Image Processing 2021 - [i1]Adrianna Janik, Jonathan Dodd, Georgiana Ifrim, Kris Sankaran, Kathleen M. Curran:
Interpretability of a Deep Learning Model in the Application of Cardiac MRI Segmentation with an ACDC Challenge Dataset. CoRR abs/2103.08590 (2021)
2010 – 2019
- 2019
- [c2]Adrianna Janik, Kris Sankaran, Anthony Ortiz:
Interpreting Black-Box Semantic Segmentation Models in Remote Sensing Applications. MLVis@EuroVis 2019: 7-11 - 2016
- [c1]Piotr Ciskowski, Adrianna Janik, Marek Bazan, Krzysztof Halawa, Tomasz Janiczek, Andrzej Rusiecki:
Estimation of Travel Time in the City Based on Intelligent Transportation System Traffic Data with the Use of Neural Networks. DepCoS-RELCOMEX 2016: 85-95
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