Layer-Wise Relevance Propagation in Multi-label Neural Networks to Identify COVID-19 Associated Coinfections

Marilyn Bello*, Yaumara Aguilera, Gonzalo Nápoles, María M. García, Rafael Bello, Koen Vanhoof

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

COVID-19 has been affected worldwide since the end of 2019. Clinical studies have shown that a factor that increases its lethality is the existence of secondary infections. Coinfections associated with the infection SARS-CoV-2 are classified into bacterial infections and fungal infections. A patient may develop one, both, or neither. From a machine learning point of view, this is considered a multi-label classification problem. In this work, we propose a multi-label neural network able to detect such infections in a patient with SARS-CoV-2 and thus provide the medical community with a diagnosis to guide therapy in these patients. However, neural networks are often considered a “black box” model, as their strength in modeling complex interactions, also make their operation almost impossible to explain. Therefore, we propose three adaptations of the Layer-wise Relevance Propagation algorithm to explain multi-label neural networks. The inclusion of this post-hoc interpretability stage made it possible to identify significant input variables in a classifier output.

Original languageEnglish
Title of host publicationProgress in Artificial Intelligence and Pattern Recognition - 7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021, Proceedings
EditorsYanio Hernández Heredia, Vladimir Milián Núñez, José Ruiz Shulcloper
PublisherSpringer Science and Business Media Deutschland GmbH
Pages3-12
Number of pages10
ISBN (Print)9783030896904
DOIs
Publication statusPublished - 2021
Event7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021 - Virtual, Online
Duration: 5 Oct 20217 Oct 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13055 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021
CityVirtual, Online
Period5/10/217/10/21

Keywords

  • Coinfections
  • COVID-19
  • Layer-wise Relevance Propagation
  • Multi-label scenario
  • Neural networks

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