Explainable Artificial Intelligence for Cytological Image Analysis

Stefan Röhrl, Hendrik Maier, Manuel Lengl, Christian Klenk, Dominik Heim, Martin Knopp, Simon Schumann, Oliver Hayden, Klaus Diepold

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

Abstract

Emerging new technologies are entering the medical market. Among them, the use of Machine Learning (ML) is becoming more common. This work explores the associated Explainable Artificial Intelligence (XAI) approaches, which should help to provide insight into the often opaque methods and thus gain trust of users and patients as well as facilitate interdisciplinary work. Using the differentiation of white blood cells with the aid of a high throughput quantitative phase microscope as an example, we developed a web-based XAI dashboard to assess the effect of different XAI methods on the perception and the judgment of our users. Therefore, we conducted a study with two user groups of data scientists and biomedical researchers and evaluated their interaction with our XAI modules, with respect to the aspects of behavioral understanding of the algorithm, its ability to detect biases and its trustworthiness. The results of the user tests show considerable improvement achieved through the XAI dashboard on the measured set of aspects. A deep dive analysis aggregated on the different user groups compares the five implemented modules. Furthermore, the results reveal that using a combination of modules achieves higher appreciation than the individual modules. Finally, one observes a user’s tendency of overestimating the trustworthiness of the algorithm compared to their perceived abilities to understand the behavior of the algorithm and to detect biases.

Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine - 21st International Conference on Artificial Intelligence in Medicine, AIME 2023, Proceedings
EditorsJose M. Juarez, Mar Marcos, Gregor Stiglic, Allan Tucker
PublisherSpringer Science and Business Media Deutschland GmbH
Pages75-85
Number of pages11
ISBN (Print)9783031343438
DOIs
StatePublished - 2023
Event21st International Conference on Artificial Intelligence in Medicine, AIME 2023 - Portoroz, Slovenia
Duration: 12 Jun 202315 Jun 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13897 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Artificial Intelligence in Medicine, AIME 2023
Country/TerritorySlovenia
CityPortoroz
Period12/06/2315/06/23

Keywords

  • Blood Cell Analysis
  • Quantitative Phase Imaging
  • XAI

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