Towards explained treatment search results: feature analysis and explanation formulation

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

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

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Abstract

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 language	English
Pages	36
Number of pages	40
Publication status	Published - 16 Jun 2021
Event	First International Workshop on eXplainable AI in Healthcare : AIME 2021 workshop - online, Porto, Portugal Duration: 16 Jun 2021 → 16 Jun 2021 Conference number: first https://www.um.es/aike/events/XAI-Healthcare/

Conference

Conference	First International Workshop on eXplainable AI in Healthcare
Abbreviated title	XAI-Healthcare
Country/Territory	Portugal
City	Porto
Period	16/06/21 → 16/06/21
Internet address	https://www.um.es/aike/events/XAI-Healthcare/

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https://research.vu.nl/en/publications/towards-explained-treatment-search-results-feature-analysis-and-e

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Contempré, E., Szlávik, Z., Velazquez Godinez, E., ten Teije, A., & Tiddi, I. (2021). Towards explained treatment search results: feature analysis and explanation formulation. 36. Paper presented at First International Workshop on eXplainable AI in Healthcare , Porto, Portugal. https://research.vu.nl/en/publications/towards-explained-treatment-search-results-feature-analysis-and-e

@conference{d9c98bca71e84df8a91d8711ff311c12,

title = "Towards explained treatment search results: feature analysis and explanation formulation",

abstract = "We are presenting preliminary results of a work-in-progress project that aims to increase healthcare professionals{\textquoteright} 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.",

author = "Edeline Contempr{\'e} and Zolt{\'a}n Szl{\'a}vik and \{Velazquez Godinez\}, Erick and \{ten Teije\}, Annette and Ilaria Tiddi",

year = "2021",

month = jun,

day = "16",

language = "English",

pages = "36",

note = "First International Workshop on eXplainable AI in Healthcare : AIME 2021 workshop, XAI-Healthcare ; Conference date: 16-06-2021 Through 16-06-2021",

url = "https://www.um.es/aike/events/XAI-Healthcare/",

}

Contempré, E, Szlávik, Z, Velazquez Godinez, E, ten Teije, A & Tiddi, I 2021, 'Towards explained treatment search results: feature analysis and explanation formulation', Paper presented at First International Workshop on eXplainable AI in Healthcare , Porto, Portugal, 16/06/21 - 16/06/21 pp. 36. <https://research.vu.nl/en/publications/towards-explained-treatment-search-results-feature-analysis-and-e>

TY - CONF

T1 - Towards explained treatment search results: feature analysis and explanation formulation

AU - Contempré, Edeline

AU - Szlávik, Zoltán

AU - Velazquez Godinez, Erick

AU - ten Teije, Annette

AU - Tiddi, Ilaria

N1 - Conference code: first

PY - 2021/6/16

Y1 - 2021/6/16

N2 - 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.

AB - 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.

M3 - Paper

SP - 36

T2 - First International Workshop on eXplainable AI in Healthcare

Y2 - 16 June 2021 through 16 June 2021

ER -

Towards explained treatment search results: feature analysis and explanation formulation

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