Predictive Tools in the Care of Blood Donors: Prevention of Vasovagal Syndrome.

Prediction in healthcare is essential in order to promote safe and quality care. Taking adequate care of blood donors, who perform an altruistic act towards society, is paramount. Therefore, the use of tools which allow to predict the risk of Vasovagal Syndrome during the act of blood donation is necessary. The objective of this study is to design a predictive engine of an expert system to determine the risk of Vasovagal Syndrome through the use of deductive methodology. Five clusters of predictors of this syndrome were obtained by applying grouping tables of the variables established by logical formulation in such a way that after combinatorial variables, 5 values were obtained for the determination of risk using a Lickert scale. With these results we could design the predictive engine that will allow the development of a computational tool to improve the quality of care of blood donors.

Elements for an Ontology of Care in the Field of Artificial Intelligence.

An ontology of care is a formal, explicit specification of a shared conceptualization. Constructing an ontology is a process that requires four elements: knowledge object, subject that knows, knowledge operation and result. These elements configure theframework to generate ontologies that can be used in Artificial Intelligence systems for care.

Dx-Care: A Device to Help in the Diagnosis of Care Problems.

The diagnosis of care problems is a complex process that involves many variables and inferences. This competence begins to acquire during the student stage, but matures later. The qualified professional continues to settle and perfect this judgment ability. Expert Systems are technologies that can help in making decisions such as diagnosis. The objective of this study is to build an Expert System in order to help in diagnosis of care problems by means of taxonomic triangulation technique. The deductive method follows three phases that result in the representation of expert knowledge through an associative network, the construction of a verified and validated prototype and, finally, the design of an app through a document of requirements specification in IEEE standard.

The Dimensions of Care: Big Data Analysis in Health Information Systems.

The axioms of care postulate energy and time as underlying entities that allow us to study the dimensions of the person as care: the sorge. Logic allows to formalize the deductive study of sorge knowledge in order to determine what are the dimensions of care. These dimensions will be the guiding framework in the analysis of big data contained in health information systems.