The Role of Explainability in Assuring Safety of Machine Learning in
Healthcare

The Role of Explainability in Assuring Safety of Machine Learning in Healthcare

1 September 2021

Papers citing "The Role of Explainability in Assuring Safety of Machine Learning in Healthcare"

12 / 12 papers shown

Title
Integrating Explainable AI in Medical Devices: Technical, Clinical and Regulatory Insights and Recommendations Dima Alattal Asal Khoshravan Azar P. Myles Richard Branson Hatim Abdulhussein Allan Tucker 29 0 0 10 May 2025
Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Models Anastasiia Grishina Vadim Liventsev Aki Härmä Leon Moonen ELM 87 0 0 10 Mar 2025
DepressionX: Knowledge Infused Residual Attention for Explainable Depression Severity Assessment Yusif Ibrahimov Tarique Anwar Tommy Yuan 49 0 0 28 Jan 2025
ASTRID -- An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems Mohita Chowdhury Yajie Vera He Aisling Higham Ernest Lim 60 1 0 14 Jan 2025
Towards Robust Training Datasets for Machine Learning with Ontologies: A Case Study for Emergency Road Vehicle Detection Lynn Vonderhaar Timothy Elvira T. Procko Omar Ochoa 39 0 0 21 Jun 2024
Designing for Complementarity: A Conceptual Framework to Go Beyond the Current Paradigm of Using XAI in Healthcare Elisa Rubegni Omran Ayoub Stefania Maria Rita Rizzo Marco Barbero G. Bernegger Francesca Faraci Francesca Mangili Emiliano Soldini P. Trimboli Alessandro Facchini 29 1 0 06 Apr 2024
What's my role? Modelling responsibility for AI-based safety-critical systems Philippa Ryan Zoe Porter Joanna Al-Qaddoumi John McDermid Ibrahim Habli 31 1 0 30 Dec 2023
AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms Dhaminda B. Abeywickrama James Wilson Suet Lee Greg Chance Peter D. Winter Arianna Manzini Ibrahim Habli Shane Windsor Sabine Hauert Kerstin Eder 22 5 0 20 Feb 2023
The Solvability of Interpretability Evaluation Metrics Yilun Zhou J. Shah 76 8 0 18 May 2022
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System Markus Borg Jens Henriksson Kasper Socha Olof Lennartsson Elias Sonnsjo Lonegren T. Bui Piotr Tomaszewski S. Sathyamoorthy Sebastian Brink M. H. Moghadam 35 23 0 16 Apr 2022
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,696 0 28 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 180 932 0 21 Oct 2016