Sensitivity of Estimators for Measuring Information Amount in Web-Based Medical Documents

Abstract

Nowadays, communication between patient and doctor during an appointment has changed significantly owning to the opportunity that medical portals provide. Whether or not necessarily appreciated by the doctors, the patients became more aware of the first symptoms’ suggesting a particular disease and the medical procedures that apply as a standard. Estimating amount of reliable factual medical information in a document is carried out by parametrizing space of digital documents and dividing it into subsequent layers that represent distribution of the system responses computed as random variables to a query about medical information. Analyzed are the following attributes: dynamism of decrease of query words numbers in the documents, precision, recall in the metric space layers, their mutual correlation and specifically the amount of reliable medical information in the documents. Sensitivity of estimators is explored in order to determine the final decision about further browsing digital documents of the metric space for more medical information that satisfies the user’s need. For identification of the true positive information in the space layer and then, in each document of this layer, matching of medical terminology with the document contents, is processed following binary Boolean search space model.