The range and use of telehealth services to remotely diagnose, manage or treat diseases have expanded over the past decades for a wide variety of populations. Telehealth includes the use of video conferencing software, telephone, patient portals and mobile health applications to deliver healthcare.
This multidisciplinary and multicentre research group´s main objectives are
- To facilitate patient-engagement in healthcare;
- To use machine learning and other methods to process big data generated by electronic medical records (EMR), registries, health platforms and medical imaging technologies;
- Apply ICTs to collect data and promote intervention studies;
- To incorporate simulation in pre and post-graduate training of healthcare professionals.
This research group is developing a deep machine learning framework to be used for radiology image pre-reading, with the purpose of:
- Releasing human resources for more complex tasks;
- Increasing human productivity on a radiology digital environment;
- Bringing up radiology care to underdeveloped regions.
They also applied narrative learning processing to assess rheumatoid arthritis’ disease activity in EMR, to establish treatment response predictors upon Reuma.pt and are applying these techniques to retrieve more relational data from patient innovation networks.
NMS and CHLC host a Simulation Centre for training of healthcare professionals. The researchers will implement several educational research studies, including:
- Trials to compare classical and EMBS resuscitation training;
- Training in obstetrics and neonatal care;
- Validation of competence-assessment instruments;
- Impact assessment of the simulation training in patient-outcomes.