The path
noze continues and consolidates its machine learning work applied to health data. The activity, initiated in previous years through specific projects, becomes a permanent operational line, joining AI and Cyber Security among the company’s business areas.
The areas of intervention
The work is structured around three main directions:
- Predictive analysis: models capable of anticipating the evolution of clinical conditions from historical and current data. The objective is to provide clinicians with tools for proactive intervention
- Classification models: machine learning algorithms for the automatic categorisation of clinical data — diagnostic images, biometric parameters, textual reports — with accuracy levels validated on real datasets
- Clinical decision support: systems that integrate the results of predictive and classification models into clinical workflows, presenting contextualised recommendations to the physician
The consolidation
The Digital Health line becomes a dedicated business area, with vertical expertise and active projects. The integration with artificial intelligence and cyber security capabilities makes it possible to address the specific challenges of the healthcare sector: from data quality to privacy protection, from clinical validation to regulatory compliance.
The context
This consolidation marks the transition from isolated projects to a structured and repeatable capability in the application of machine learning to the healthcare domain.