{"type":"ScholarlyArticle","title":"ACTA A Tool for Argumentative Clinical Trial Analysis","authors":[{"name":"Tobias Mayer","slug":"tobias-mayer","given":"Tobias","family":"Mayer","affiliation":"Université Côte d'Azur , CNRS , Inria , I3S , France"},{"name":"Elena Cabrio","slug":"elena-cabrio","given":"Elena","family":"Cabrio","affiliation":"Université Côte d'Azur , CNRS , Inria , I3S , France"},{"name":"Serena Villata","slug":"serena-villata","given":"Serena","family":"Villata","affiliation":"Université Côte d'Azur , CNRS , Inria , I3S , France"}],"abstract":"Argumentative analysis of textual documents of various nature (e.g., persuasive essays, online discussion blogs, scientific articles) allows to detect the main argumentative components (i.e., premises and claims) present in the text and to predict whether these components are connected to each other by argumentative relations (e.g., support and attack), leading to the identification of (possibly complex) argumentative structures. Given the importance of argument-based decision making in medicine, in this demo paper we introduce ACTA, a tool for automating the argumentative analysis of clinical trials. The tool is designed to support doctors and clinicians in identifying the document(s) of interest about a certain disease, and in analyzing the main argumentative content and PICO elements.","doi":"10.24963/ijcai.2019/953","url":"https://ijcai.org/proceedings/2019/953","pdf":"https://ijcai.org/proceedings/2019/0953.pdf","markdown":"https://ijcai.org/proceedings/2019/953.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/953","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Demos","track":"Demos","number":953,"pages":{"first":6551,"last":6553},"keywords":["Applications: Medical and healthcare","AI: Natural Language Processing"],"videos":[],"references":[{"position":1,"raw":"[Atkinson et al., 2017] Katie Atkinson, Pietro Baroni, Mas- similiano Giacomin, Anthony Hunter, Henry Prakken, Chris Reed, Guillermo Ricardo Simari, Matthias Thimm, and Serena Villata. 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