Summary of the technology
The software addresses the need to identify the risk of developing Alzheimer's disease in patients at
an early stage of life, which can be crucial for implementing preventive interventions and more
effective treatment, but above all for planning in advance the legacy that the affected person will leave
to their family and loved ones, as well as for making the best decisions together for both parties.
Using a machine learning algorithm trained with data from the GERO cohort, the software has the
ability to predict the risk of a patient developing Alzheimer's disease at an early age. It is based on
dimensionality reduction techniques to analyze a panel of microRNA data from the GERO cohort,
which includes information on mental health, laboratory chemistry measurements, and other relevant
variables. This approach allows the software to generate accurate and personalized predictions about
the risk of Alzheimer's for each patient, which can guide clinical decisions and improve health
outcomes.
Details of the Technology Offer
TRL: 4
Aplications
Medical diagnostics.
Health sciences.
Machine Learning development.
Advantages
Allows for early preventive measures.
High accuracy.
It reduces results bias.
Further research required
We are looking for enterprises that are willing to invest and develop this technology to a higher TRL
Current development status
Working prototypes
Attached documents
Related Keywords