HEALTHCARE COLLABORATIVE E-LEARNING PLATFORM FOR TREATING BLOOD PRESSURE DISEASES

Health virtual communities empower the medical staff, doctors and their students to be connected and enhance the coordination of treatments. These communities appeared in the middle of the 90' s. Further challenges appeared since that time when implementing the electronic health records and while integrating them to several health providers. The medical students are able to confront different real situations and handle their knowledge for healing patients who suffer from blood pressure diseases. Preeclampsia is a disease characterized by high blood pressure and it occurs in the last trimester of pregnancy. It is one of the main reasons of death for the mother and infant. The communication with the patients is sustained, bringing better outcomes for their health state, while being away from hospitals. No matter the geographical position, the members of the community share their knowledge inside a virtual organizational platform. The interaction between the patient and the doctors is sustained and their health state is better monitored. The practical training of the medical students is also done via the collaborative e-learning platform. Medical forums of the e-learning platform where the patients who suffer from blood pressure diseases (hypo and hypertension), as well as pregnant women who suffer due to preeclampsia are parsed for assessing the common illness symptoms. From their postings are extracted the relevant features which are further used for the semantic matching process between the symptoms and the associated treatment. The treatment given by doctors is also passed in order to extract the existent solutions. Information retrieval processes are performed on the medical forum postings. Models are created for the users and the provided illness treatments. Each user is associated to possible treatments based on the triggered metrics obtained after performing the matching. The NoSQL database, MongoDB, is used to store the complete forum postings, while Elasticsearch stores the parameters which are used when performing the matching. These parameters are obtained using the term frequency - inverse document frequency statistic to determine the importance of a word in a corpus of postings. Elasticsearch documents which have the JSON format share the same IDs as their MongoDB counterparts. The paper describes the exploiting of the medical collaborative e-learning platform that proves to be very efficient and convenient for the members which do not have to physically meet and whom can help one another. A significant value is added to health informatics. The quality of life for the persons is sustained inside the virtual collaborative e-learning platform where the medical students can learn new ways of treating their patients.