Healthcare Data Sources and Basic Analytics: These chapters discuss the details about the various healthcare data sources and the analytical techniques that are widely used in the processing and analysis of such data. The various forms of patient data include electronic health records, biomedical images, sensor data, biomedical signals, genomic data, clinical text, biomedical literature, and data gathered from social media.Advanced Data Analytics for Healthcare: These chapters deal with the advanced data analytical methods focused on healthcare. These in..
The development of Health Information Systems based on dual models allows modifications to be conducted in the layer of archetypes, reducing dependencies on software developers. However, we identified a lack of conceptual models to represent two-level database entities. This paper proposes a novel conceptual data model, called ArcheER, which is a dual modeling approach and aims to reduce redundant entities and guarantee the creation of unique electronic health records. ArcheER is an extension of the Entity-Relationship model and is based on archetypes. A..
The rising cost of health care is one of the world’s most important problems. Accordingly, predicting such costs with
accuracy is a significant first step in addressing this problem. Since the 1980s, there has been research on the predictive
modeling of medical costs based on (health insurance) claims data using heuristic rules and regression methods. These
methods, however, have not been appropriately validated using populations that the methods have not seen. We utilize
modern data-mining methods, specifically classification trees and clustering algori..