Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition.

Previous work on clinical relation extraction from free-text sentences leveraged information about semantic types from clinical knowledge bases as a part of entity representations. In this paper, we exploit additional evidence by also making use of . We encode the relation between a span of tokens matching a Unified Medical Language System (UMLS) concept and other tokens in the sentence.

Can the crowd judge truthfulness? A longitudinal study on recent misinformation about COVID-19.

Recently, the misinformation problem has been addressed with a crowdsourcing-based approach: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd of non-expert is exploited. We study whether crowdsourcing is an effective and reliable method to assess truthfulness during a pandemic, targeting statements related to COVID-19, thus addressing (mis)information that is both related to a sensitive and personal issue and very recent as compared to when the judgment is done. In our experiments, crowd workers are asked to assess the truthfulness of statements, and to provide evidence for the assessments.

Health Cards to Assist Decision Making in Consumer Health Search.

We investigate the effectiveness of health cards to assist decision making in Consumer Health Search (CHS). A health card is a concise presentation of a health concept shown along side search results to specific queries. We specifically focus on the decision making tasks of determining the health condition presented by a person and determining which action should be taken next with respect to the health condition.

Novel insights into views towards H1N1 during the 2009 Pandemic: a thematic analysis of Twitter data.

Background: Infectious disease outbreaks have the potential to cause a high number of fatalities and are a very serious public health risk.

Objectives: Our aim was to utilise an indepth method to study a period of time where the H1N1 Pandemic of 2009 was at its peak.

Methods: A data set of n = 214 784 tweets was retrieved and filtered, and the method of thematic analysis was used to analyse the data.

The natural antioxidant alpha-lipoic acid induces p27(Kip1)-dependent cell cycle arrest and apoptosis in MCF-7 human breast cancer cells.

Unlike normal cells, tumor cells survive in a specific redox environment where the elevated reactive oxygen species contribute to enhance cell proliferation and to suppress apoptosis. Alpha-lipoic acid, a naturally occurring reactive oxygen species scavenger, has been shown to possess anticancer activity, due to its ability to suppress proliferation and to induce apoptosis in different cancer cell lines. Since at the moment little information is available regarding the potential effects of alpha-lipoic acid on breast cancer, in the present study we addressed the question whether alpha-lipoic acid induces cell cycle arrest and apoptosis in the human breast cancer cell line MCF-7.