The digitization of healthcare results in the collection of large amounts of data on people’s illnesses and treatments. This significant amount of information creates new possibilities and opportunities for managing public healthcare more efficiently and innovatively.
With this in mind, Almaviva has built a platform that enables advanced analysis of data from various sources. In particular, by collecting and processing clinical data from hospitalized patients, it was possible to implement predictive machine learning algorithms to predict the occurrence of chronic diseases and support at-home monitoring and care.
Advanced data collection and analysis
Predictive machine learning algorithms
Support for at-home monitoring and care
The new portal is equipped with machine learning technologies that can anticipate the onset of certain diseases. It also allows for more efficient management of monitoring based on patient histories, speeding up chronic care intakes and increasing the quality of at-home care and telemedicine, with advantages for the efficiency of the national health system.
Prediction of chronic diseases
Smoother intake management
Improved quality of at-home care and telemedicine