Pilot 1.1

The Pilot 1.1- Leveraging data for clinical decision support system and data management leverages a variety of tools, skills and knowledge to design and develop effective and efficient healthcare solutions. More in detail, The Pilot 1.1 develops and applies artificial intelligence, machine learning, deep learning models and algorithms for clinical decision support systems and data management, to help and support the healthcare domain to make personalized and explainable decisions for both diagnosis and prognosis of several impactful and costly chronic diseases.

Fundamental issues related to healthcare data are given great attention as privacy, fairness, quality, and reliability. Indeed, data collection, validation and quality assessment are the core of the data centric objectives of the Spoke 1 – Data and technology driven diagnosis and therapies. Guidelines and requirements are developed for the subsequent data collection, validation, protection and processing phases, performed by other pilots of the Spoke 1. In this regard, the Pilot 1.1 supports the responsible and effective management of such data.

Artificial Intelligence, machine learning, deep learning, natural language processing and causal networks will be leveraged to design and develop decision making support systems for different diseases, with specific attention to those that are the focus of the other pilots of Spoke 1.

In summary, the main activities of Pilot 1.1 concern the formulation of complex decision making problems in such a manner that they can be tackled and solved by data-driven models and algorithms. It is worthwhile to mention that the approach is almost always with the so called “human in the loop”: this means that the designed and developed models, algorithms and solutions will support and help the decision maker, the medical doctor, while not aiming to replace her/him but with the only goal to augment her/his capability and effectiveness to make decisions under complex settings.