Towards explainable artificial intelligence and explanation user interfaces to open the ‘black box’ of automated ECG interpretation

Khaled Rjoob, RR Bond, D Finlay, V. E. McGilligan, Stephen James Leslie, Ali Rababah, Aleeha Iftikhar, D Guldenring, Charles Knoery, Anne McShane, Aaron Peace

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This an exploratory paper that discusses the use of artificial intelligence (AI) in ECG interpretation and opportunities for improving the explaina-bility of the AI (XAI) when reading 12-lead ECGs. To develop AI systems, many principles (human rights, well-being, data agency, effectiveness, transparency, accountability, awareness of misuse and competence) must be considered to ensure that the AI is trustworthy and applicable. The current computerised ECG interpretation algorithms can detect different types of heart diseases. However, there are some challenges and shortcomings that need to be addressed, such as the explainability issue and the interaction between the human and the AI for clinical decision making. These challeng-es create opportunities to develop a trustworthy XAI for automated ECG interpretation with a high performance and a high confidence level. This study reports a proposed XAI interface design in automatic ECG interpreta-tion based on suggestions from previous studies and based on standard guidelines that were developed by the human computer interaction (HCI) community. New XAI interfaces should be developed in the future that fa-cilitate more transparency of the decision logic of the algorithm which may allow users to calibrate their trust and use of the AI system.
Original languageEnglish
Title of host publicationAdvanced Visual Interfaces. Supporting Artificial Intelligence and Big Data Applications
Subtitle of host publicationAVI 2020 Workshops, AVI-BDA and ITAVIS, Ischia, Italy, June 9, 2020 and September 29, 2020, Revised Selected Papers
EditorsThoralf Reis, Marco X. Bornschlegl, Marco Angelini, Matthias L. Hemmje
PublisherSpringer
Chapter6
Volume12585
Edition1
ISBN (Electronic)978-3-030-68007-7
ISBN (Print)978-3-030-68006-0
Publication statusAccepted/In press - 15 May 2020
EventWorkshop on Road Mapping Infrastructures for Artificial Intelligence Supporting Advanced Visual Big Data Analysis -
Duration: 9 Jun 2021 → …
https://avi2020.ftk.de/

Publication series

NameInformation Systems and Applications, incl. Internet/Web, and HCI
PublisherSpringer International Publishing
Volume12585

Conference

ConferenceWorkshop on Road Mapping Infrastructures for Artificial Intelligence Supporting Advanced Visual Big Data Analysis
Abbreviated titleAVI-BDA
Period9/06/21 → …
Internet address

Keywords

  • explainable artificial intelligence
  • XAI
  • ECG
  • decision support systems

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