Towards explained treatment search results: feature analysis and explanation formulation

Edeline Contempré*, Zoltán Szlávik, Erick Velazquez Godinez, Annette ten Teije*, Ilaria Tiddi

*Corresponding author for this work

Research output: Contribution to ConferencePaperAcademic

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We are presenting preliminary results of a work-in-progress project that aims to increase healthcare professionals’ trust in treatment search engines by introducing a) explainability based re-ordering of re- trieved documents, and b) providing user-friendly explanations for each of these documents. Through the use of crowdsourcing, we assess the importance of various features for explainability, and also investigate as- pects of explanation formulation as presented to end-users. Our results allow us to determine feature weights that will be inputs to the document re-ordering model, the per-document explanatory sentence formulation module, and the sentence ordering model.
Original languageEnglish
Number of pages40
Publication statusPublished - 16 Jun 2021
EventFirst International Workshop on eXplainable AI in Healthcare : AIME 2021 workshop - online, Porto, Portugal
Duration: 16 Jun 202116 Jun 2021
Conference number: first


ConferenceFirst International Workshop on eXplainable AI in Healthcare
Abbreviated titleXAI-Healthcare
Internet address

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