Data science, analytics and artificial intelligence in e-health : trends, applications and challenges

Acknowledgments. This work has been partially supported by the Divina Pastora Seguros company.More than ever, healthcare systems can use data, predictive models, and intelligent algorithms to optimize their operations and the service they provide. This paper reviews the existing literature regarding the use of data science/analytics methods and artificial intelligence algorithms in healthcare. The paper also discusses how healthcare organizations can benefit from these tools to efficiently deal with a myriad of new possibilities and strategies. Examples of real applications are discussed to illustrate the potential of these methods. Finally, the paper highlights the main challenges regarding the use of these methods in healthcare, as well as some open research lines

Using Matrix Decompositions in Formal Concept Analysis

Abstract. One of the main problems connected with the formal concept analysis and lattice construction is the high complexity of algorithms which plays a significant role when computing all concepts from a huge incidence matrix. In some cases, we only need to compute some of them to test for common attributes. In our research we try to modify an incidence matrix using matrix decompositions, creating a new matrix with fewer dimensions as an input for some known algorithms for lattice construction. In this paper, we want to describe methods of matrix decompositions and their influence on the concept lattice