Information extraction from electronic medical documents: state of the art and future research directions.

In the medical field, a doctor must have a comprehensive knowledge by reading and writing narrative documents, and he is responsible for every decision he takes for patients. Unfortunately, it is very tiring to read all necessary information about drugs, diseases and patients due to the large amount of documents that are increasing every day. Consequently, so many medical errors can happen and even kill people.

Parallel social behavior-based algorithm for identification of influential users in social network.

Influence maximization in social networks refers to the process of finding influential users who make the most of information or product adoption. The social networks is prone to grow exponentially, which makes it difficult to analyze. Critically, most of approaches in the literature focus only on modeling structural properties, ignoring the social behavior in the relations between users.

Epidemiology and Whole-Genome Analysis of -Producing KP3771 from Tunisia.

The whole-genome sequence (WGS) of KP3771 isolate was characterized. This strain was recovered from the urine sample of an 80-year-old man hospitalized in an intensive care unit of the University Hospital Tahar Sfar in Tunisia. WGS using a MiSeq platform was used.

A softmin-based neural model for causal reasoning.

This paper extends a neural model for causal reasoning to mechanize the monotonic class. Hence, the resulting model is able to solve multiple, varied causal problems in the open, independent, incompatibility and monotonic classes. First, additivity between causes is formalized as a fuzzy AND-ing process.