Adrianna Janik

According to our database, Adrianna Janik authored at least 13 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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., January, 2024

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, Mariano Provencio, Vít Novácek

J. Biomed. Informatics, August, 2023

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, Edel del Barco, Joaquim Bosch-Barrera, Vít Novácek

Proceedings of the International Joint Conference on Neural Networks, 2023

2022

Explaining Link Predictions in Knowledge Graph Embedding Models with Influential Examples.

Adrianna Janik, Luca Costabello

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, Edel del Barco, Joaquim Bosch-Barrera, Ernestina Menasalvas, Mohan Timilsina, Mariano Provencio

CoRR, 2022

Sampling Strategy for Fine-Tuning Segmentation Models to Crisis Area under Scarcity of Data.

Adrianna Janik, Kris Sankaran

CoRR, 2022

Discovering Concepts in Learned Representations using Statistical Inference and Interactive Visualization.

Adrianna Janik, Kris Sankaran

CoRR, 2022

Unsupervised Customer Segmentation with Knowledge Graph Embeddings.

Sumit Pai, Fiona Brennan, Adrianna Janik, Teutly Correia, Luca Costabello

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

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, Reyes Bernabé, Maria Guirado, Pasquale Minervini, Vít Novácek

Proceedings of the AMIA 2022, 2022

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

Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021

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

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2019

Interpreting Black-Box Semantic Segmentation Models in Remote Sensing Applications.

Adrianna Janik, Kris Sankaran, Anthony Ortiz

Proceedings of the 2nd Workshop on Machine Learning Methods in Visualisation for Big Data, 2019

2016

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

Proceedings of the Dependability Engineering and Complex Systems, 2016