Informed healthcare decisions with evidence based real-time data and long term monitoring are of interest for society as they provide new ways to monitor patients and to try out and prescribe treatment. For supporting high quality medical/healthcare services, reliable measurements can act as a trustworthy informed decision base for patient-doctor communication, physically and/or remotely. The quality of measurements of personal mobile sensors, e.g., glucose or heart rate, needs to fulfill certain requirements such as the systems storing and analyzing the data. Qualities like, e.g., integrity and safety, are managed with healthcare assurance and certificate systems. They consider a wide variety of individuals/patients with diverse interest, knowledge, and cognitive level.
The goal for the researchers within eHealth – Improved Data to and from Patients is to generate new knowledge on how to model, engineer, visualize and validate systems and tools for supporting healthcare applications in for example the fields of diabetes and medication. This research will result in novel ways for systematic data collection, monitoring and visualization of different medical values.
Analyzing data with mining techniques
Open/personalized, real-time/registered data is collected from a variety of systems (health-care records, mobile sensors) and their environments. The data is analyzed using different mining techniques combined with visual analytics.
This type of research needs clinical competence related to the interpretation and trust of data that is generated automatically or by the individuals respectively. This is supplemented by system and data analysis and visualization competences from computer scientists. External partners will provide access to national quality registers and clinical data output from electronic patient records.
eHealth – Improved Data to and from Patients is an application area within the Linnaeus University Centre of Excellence (LNUC) for Data Intensive Sciences and Applications.
At DISA, we encourage and support seed projects. Seed projects are intended to promote and nurture excellence research, development and innovation within data intensive sciences and applications with cross-discipline collaboration.
Seed projects at eHealth
- Cecilia Fagerström Professor
- Diego Perez Palacin Senior lecturer
- Göran Petersson Senior professor
- Ilir Jusufi Senior lecturer
- Jan Aidemark Senior Lecturer
- Jenny Lundberg Senior Lecturer
- Linda Askenäs Senior lecturer
- Marcelo Milrad Professor, Vice-dean
- Martin Carlsson Associate professor
- Mirjam Ekstedt Professor
- Niclas Eberhagen Senior Lecturer
- Ola Nordqvist Doctoral student
- Olof Björneld Doctoral student
- Tora Hammar Senior lecturer
- Viktor Kaldo Professor
Maria Thunander, Region Kronoberg