Abstract
Today, almost every human activity generates and/or demands to store and process massive, diverse and complex data, either in scientific, academic, enterprise and even leisure pursuits - the scenario being called as the “big data era”. Health-related activities are in the core of those activities, as they produce big data as well as they can take advantage of the technological storm, improving the behavior of everyone whose decision is increasingly guided by the information extracted from all these big data. In a clinical environment, the Electronic Health Records (EHR) forms a proper anchor to develop information extraction strategies. In this proposal, we aim at integrating novel database support, image processing and visual analytics methods to leverage the large number of EHR and repositories of clinical data to gather valuable and significant information for decision-making. The size and complexity of EHR databases offer great challenges when they need to be processed in terms both of applying analysis techniques and to support the development of subsequent applications for practical tools. However, it also embodies a cornucopia of opportunities to create algorithms and methods able to display smart and relevant information related to either a particular patient or groups of patients and to boost the EHR into a more effective platform to support the healthcare professionals, coping medical applications and strategic government decisions with the demands and benefits of big data. In this project we will develop methods and algorithms that will ultimately be materialized as a modular platform to be made available to the community. (AU)
| Articles published in Agência FAPESP Newsletter about the research grant: |
| More itemsLess items |
| TITULO |
| Articles published in other media outlets ( ): |
| More itemsLess items |
| VEICULO: TITULO (DATA) |
| VEICULO: TITULO (DATA) |