Search Results for author: Adrianna Janik

Found 5 papers, 1 papers with code

Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients

no code implementations17 Nov 2022 Adrianna Janik, Maria Torrente, Luca Costabello, Virginia Calvo, Brian Walsh, Carlos Camps, Sameh K. Mohamed, Ana L. Ortega, Vít Nováček, Bartomeu Massutí, Pasquale Minervini, M. Rosario Garcia Campelo, Edel del Barco, Joaquim Bosch-Barrera, Ernestina Menasalvas, Mohan Timilsina, Mariano Provencio

Conclusions: Our results show that machine learning models trained on tabular and graph data can enable objective, personalised and reproducible prediction of relapse and therefore, disease outcome in patients with early-stage NSCLC.

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

no code implementations9 Feb 2022 Adrianna Janik, Kris Sankaran

We have applied our method to a deep learning model for semantic segmentation, U-Net, in a remote sensing application of building detection - one of the core use cases of remote sensing in humanitarian applications.

Active Learning Humanitarian +2

Discovering Concepts in Learned Representations using Statistical Inference and Interactive Visualization

1 code implementation9 Feb 2022 Adrianna Janik, Kris Sankaran

Among current formulations, concepts defines them by as a direction in a learned representation space.

Navigate

Interpretability of a Deep Learning Model in the Application of Cardiac MRI Segmentation with an ACDC Challenge Dataset

no code implementations15 Mar 2021 Adrianna Janik, Jonathan Dodd, Georgiana Ifrim, Kris Sankaran, Kathleen Curran

In previous studies, the base method is applied to the classification of cardiac disease and provides clinically meaningful explanations for the predictions of a black-box deep learning classifier.

MRI segmentation

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