activity
20222024
most citedImpact of Feedback Type on Explanatory Interactive Learning

8 citations · 22 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2024★ 7 cited

An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data

Niamh Belton, Aonghus Lawlor, Kathleen M. Curran

The diagnostic accuracy and subjectivity of existing Knee Osteoarthritis (OA) ordinal grading systems has been a subject of on-going debate and concern. Existing automated solution…

eess.IV2024★ 1 cited

Rethinking Knee Osteoarthritis Severity Grading: A Few Shot Self-Supervised Contrastive Learning Approach

Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor +1

Knee Osteoarthritis (OA) is a debilitating disease affecting over 250 million people worldwide. Currently, radiologists grade the severity of OA on an ordinal scale from zero to fo…

eess.IV2024

Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach

Anam Hashmi, Julia Dietlmeier, Kathleen M. Curran +1

Cine cardiac magnetic resonance (CMR) imaging is recognised as the benchmark modality for the comprehensive assessment of cardiac function. Nevertheless, the acquisition process of…

cs.CV2023

Distance-Aware eXplanation Based Learning

Misgina Tsighe Hagos, Niamh Belton, Kathleen M. Curran +1

eXplanation Based Learning (XBL) is an interactive learning approach that provides a transparent method of training deep learning models by interacting with their explanations. XBL…

eess.IV2023

Unlearning Spurious Correlations in Chest X-ray Classification

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee

Medical image classification models are frequently trained using training datasets derived from multiple data sources. While leveraging multiple data sources is crucial for achievi…

cs.LG2023

Learning from Exemplary Explanations

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee

eXplanation Based Learning (XBL) is a form of Interactive Machine Learning (IML) that provides a model refining approach via user feedback collected on model explanations. Although…

eess.IV2023

Interpretable Weighted Siamese Network to Predict the Time to Onset of Alzheimer's Disease from MRI Images

Misgina Tsighe Hagos, Niamh Belton, Ronan P. Killeen +2

Alzheimer's Disease (AD) is a progressive disease preceded by Mild Cognitive Impairment (MCI). Early detection of AD is crucial for making treatment decisions. However, most of the…

cs.LG2023★ 1 cited

FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks

Niamh Belton, Misgina Tsighe Hagos, Aonghus Lawlor +1

Recent Anomaly Detection techniques have progressed the field considerably but at the cost of increasingly complex training pipelines. Such techniques require large amounts of trai…

cs.CV2022★ 5 cited

Identifying Spurious Correlations and Correcting them with an Explanation-based Learning

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee

Identifying spurious correlations learned by a trained model is at the core of refining a trained model and building a trustworthy model. We present a simple method to identify spu…

cs.AI2022★ 8 cited

Impact of Feedback Type on Explanatory Interactive Learning

Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee

Explanatory Interactive Learning (XIL) collects user feedback on visual model explanations to implement a Human-in-the-Loop (HITL) based interactive learning scenario. Different us…