ACTA* (cite) is a tool designed to ease the work of clinicians in analyzing clinical trials. It goes beyond the basic keyword-based search in clinical trial abstracts, and it empowers the clinician with the ability to retrieve the main claim(s) stated in the trial, as well as the premises (or evidence) linked to this claim. As a result, the clinician does not need to read the whole abstract, but she is provided with a structured “summary” of the abstract under the form of a graph. To know more about ACTA, have a look at our paper. The tool provides the user with the following facilities:
PubMed is a free search engine accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. Given the importance of this search engine in the health-care domain, we included in ACTA the possibility to search for a (set of) abstract(s) directly on the PubMed catalogue, through their API. When the search results are shown, the user can select one or more abstracts to address the argumentative analysis.
As soon as the text is uploaded or the abstract(s) is selected from the PubMed search result list, the user can run the argumentative analysis by pressing the analyse-button. The result is visualized to the user under the form of an argumentative graph where the nodes are the premises and the claims automatically detected in the abstract together with their links. The textual content of the argumentative component is shown, when the user hovers over a node. In addition, the full text of the abstract is shown on the right side of the graph, where premises and claims are highlighted with different colors.
In addition, given the importance of the PICO information for the health-care domain, we automatically detect PICO elements in the text of the clinical trial. These elements are highlighted in different colors on the right.
*This work is partly funded by the French government labelled PIA program under its IDEX UCA JEDI project (ANR-15- IDEX-0001).
Use the PubMed Search to query the database at the National Center for Biotechnology Information (NCBI). We show the latest 49 entries, which match the query. Select one or more documents for the argumentative analysis in the next step.
Enter your own text in the text box and apply the argument mining pipeline on that.
Browse a collection of already processed documents to get a quick overview. Select from a list of PubMed IDs on the left to display the argument graph and the annotated abstract.