Document Analysis for Evidence Based Medicine. A proposal with Big Data Analytics

Abstract

Big data analytics is a technology that includes the storage, administration and analysis of large volumes of data, its application in the field of health has been recent. This paper focuses on a proposal for analysis of three-phase documents: diagnosis, analysis and evaluation. The proposal forms part of a thesis work under development, which has identified the data sources for its analysis as Cochrane, ACP Journal, PUBMED. Also the analysis techniques to use as Support vector machines, Naive Bayes and Cluster k-means. As well as evaluation techniques such as confusion matrix and ROC curve. This proposal is a support in the decision making for the health professionals, allowing them to make better medical diagnoses.