Machine Learning

The developed solution is an innovative web application that leverages advanced Explainable Machine Learning algorithms to enable rapid, early diagnosis of Alzheimer’s disease, anticipating symptomatic onset by up to 18 months. At the core of the technology is the integration of a gender-specific approach combined with the exclusive use of non-invasive, cost-effective data, such as neuropsychological test scores.

Using network science and machine learning, we studied how companies move within the technology space during mergers and acquisitions. We validated this methodology by predicting which pairs of companies will enter into an agreement and, given an acquirer, which company will be its target. Our approach can be used to decide which company to invest in based on their respective technological activities.