Relapse prediction involves identifying factors, patterns, and bio markers that may indicate an elevated risk of symptom relapse or exacerbation.
Medteryx’s early stage AI R&D focus and model development for relapse prediction is on developing proprietary approaches to analyse large data sets of relevant patient data such as
- Demographic information
- Treatment history
- Recent patient clinical records
- Self reported patient experience (PREMSs) and outcomes (PROMs) measures
- Behavioural patterns
- Physiological markers
- Social media content and forum participation
- Smart phone / wearable monitors data for mood, mobility, sleep, and activity levels
What we do
We apply our AI R&D know-how to develop tools that analyse relevant clinical & patient data sets to identify markers of relapse risk such as
- Mood changes
- Social isolation
- Increased negative affect
- Mental health new models of care
