Local Explanations for Clinical Search Engine Results

Edeline Contempré, Zoltán Szlávik, Majid Mohammadi, Erick Velazquez, Annette Ten Teije, Ilaria Tiddi

2022

Abstract

Health care professionals rely on treatment search engines to efficiently find adequate clinical trials and early access programs for their patients. However, doctors lose trust in the system if its underlying processes are unclear and unexplained. In this paper, a model-agnostic explainable method is developed to provide users with further information regarding the reasons why a clinical trial is retrieved in response to a query. To accomplish this, the engine generates features from clinical trials using by using a knowledge graph, clinical trial data and additional medical resources. Moreover, a crowd-sourcing methodology is used to determine features’ importance. Grounded on the proposed methodology, the rationale behind retrieving the clinical trials is explained in layman’s terms so that healthcare processionals can effortlessly perceive them. In addition, we compute an explainability score for each of the retrieved items, according to which the items can be ranked. The experiments validated by medical professionals suggest that the proposed methodology induces trust in targeted as well as in non-targeted users, and provide them with reliable explanations and ranking of retrieved items.

Paper Citation

in Harvard Style

Contempré E., Szlávik Z., Mohammadi M., Velazquez E., Teije A. and Tiddi I. (2022). Local Explanations for Clinical Search Engine Results. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF; ISBN 978-989-758-552-4, SciTePress, pages 735-742. DOI: 10.5220/0010982000003123

in Bibtex Style

@conference{healthinf22,
author={Edeline Contempré and Zoltán Szlávik and Majid Mohammadi and Erick Velazquez and Annette Ten Teije and Ilaria Tiddi},
title={Local Explanations for Clinical Search Engine Results},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF},
year={2022},
pages={735-742},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010982000003123},
isbn={978-989-758-552-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF
TI - Local Explanations for Clinical Search Engine Results
SN - 978-989-758-552-4
AU - Contempré E.
AU - Szlávik Z.
AU - Mohammadi M.
AU - Velazquez E.
AU - Teije A.
AU - Tiddi I.
PY - 2022
SP - 735
EP - 742
DO - 10.5220/0010982000003123
PB - SciTePress