Abstract:

The involvement of big data analytics in healthcare enhances education by offering an improved assessment of the health cases where several virtual communities contribute with knowledge and data. In the current paper big data is used to study the appearance of preeclampsia during pregnancies and how it can be treated for positive outcomes, as well to be prevented and to cut down the costs. The clinical professors, including their university students who study medicine investigate the case of every patient in order to treat preeclampsia at an early stage. Healthcare data analytics helps at the creation of a comprehensive patient file and aims to collect the achieves about every one of them from every visited hospital and clinic. The cost of gathering much big amounts of medical data implies high costs and it is time consuming, but the technologies of today can offer educational solutions and ease the life of many persons. The virtual learning environment uses big data analytics to find treatments, keep track of past records and empower patients by involving them to take care of their own health. The students have access to the input data which is loaded from the system's ontology about diseases, medicine, symptoms and treatments into the Hadoop file system. Apache Hive is used for querying and managing patient history, the test results, the treatment options, genetics and protein datasets inside the distributed environment. After gathering this data, the patient is monitored and the treatment is adjusted, being a source of knowledge for the virtual communities, namely the clinical professors and for their students. This analytics tool helps the clinical professors and their supervised students to understand the process of treating a patient and to enhance their digital skills. The proposed system is a distributed one and it can be deployed around the world at different healthcare hospitals and clinics for learning about the innovative treatments for preeclampsia and educating the novice doctors.

Keywords:

Big data, preeclampsia, distributed healthcare system, analytics tool, virtual communities.