MAYER , Tobias

In the latest years, the healthcare domain has seen an increasing interest in the definition of intelligent systems to support clinicians in their everyday tasks and activities. Among others, this includes novel systems for the field of Evidence-based Medicine. The latter relies on the principle of critically appraising medical evidence and...

Recent advances in language model (LM) pre-training from large-scale corpora have shown to improve various natural language processing tasks. They achieve performances comparable to non-expert humans on the GLUE benchmark for natural language understanding (NLU). While the improvement of the different contextualized representations comes from...

In the latest years, the healthcare domain has seen an increasing interest in the definition of intelligent systems to support clinicians in their everyday tasks and activities. Among others, this includes novel systems for the field of Evidence-based Medicine. The latter relies on the principle of critically appraising medical evidence and...

Randomized Controlled Trials (RCT) are a common type of experimental studies in the medical domain for evidence-based decision making. The ability to automatically extract the arguments proposed therein can be of valuable support for clinicians and practitioners in their daily evidence-based decision making activities. Given the peculiarity of...

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...

Nous présentons des résumés en français et en anglais de l'article (Mayer et al., 2020) présenté à la conférence 24th European Conference on Artificial Intelligence (ECAI-2020) en 2020.

Argument(ation) Mining (AM) typically aims at identifying argumentative components in text and predicting the relations among them. Evidence-based decision making in the health-care domain targets at supporting clinicians in their deliberation process to establish the best course of action for the case under evaluation. Although the reasoning...

In the latest years, the healthcare domain has seen an increasing interest in the definition of intelligent systems to support clinicians in their everyday tasks and activities. Among others, also the field of Evidence-Based Medicine is impacted by this twist, with the aim to combine the reasoning frameworks proposed thus far in the field with...

In the last years, several empirical approaches have been proposed to tackle argument mining tasks, e.g., argument classification, relation prediction, argument synthesis. These approaches rely more and more on language models (e.g., BERT) to boost their performance. However, these language models require a lot of training data, and size is...

Evidence-based medicine aims at making decisions about the care of individual patients based on the explicit use of the best available evidence in the patient clinical history and the medical literature results. Argumentation represents a natural way of addressing this task by (i) identifying evidence and claims in text, and (ii) reasoning upon...

Argument-based decision making has been employed to support a variety of reasoning tasks over medical knowledge. These include evidence-based justifications of the effects of treatments, the detection of conflicts in the knowledge base, and the enabling of uncertain and defeasible reasoning in the health-care sector. However, a common...

The unprecedented mobilization of scientists, consequent of the COVID-19 pandemics, has generated an enormous number of scholarly articles that is impossible for a human being to keep track and explore without appropriate tool support. In this context, we created the Covid-on-the-Web project, which aims to assist the access, querying, and sense...

Le projet Covid-on-the-Web permet aux chercheurs d'accéder à la littérature relative à la famille des coronavirus, de l'interroger et d'en extraire des connaissances. Il s'aligne sur des besoins concrets formulés par des instituts de santé et de recherche. Ainsi, il adapte, combine et étend des outils destinés à traiter, analyser et enrichir le...

The Covid-on-the-Web project allows scientists to access, query and extract knowledge from the literature on the coronavirus family. It is aligned with concrete needs formulated by health and research institutes. Thus, it adapts, combines and extends tools designed to process, analyze and enrich the CORD-19 corpus, that gathers 100,000+...

Scientists are harnessing their multidisciplinary expertise and resources to fight the COVID-19 pandemic. Aligned with this mind-set, the Covid-on-the-Web project aims to allow biomedical researchers to access, query and make sense of COVID-19 related literature. To do so, it adapts, combines and extends tools to process, analyze and enrich the...