The feature extraction capabilities of Machine Learning (ML) models have led to their wide adoption in a large variety of sectors: from anomaly detection for machinery, to user clustering and behavioral prediction, market trends predictions, or the analysis of text, sound, and image data.

In the world of finance, where every decision can have significant ramifications, the possibility of predicting market movements is invaluable. Traditionally, analysts have relied on a combination of data analysis, market trends, and expert insights to make informed predictions.

Due to its multivariate and multipurpose use and reuse, data’s worth is dramatically increasing, leading to an era characterized by the generation of data marketplaces towards accessing, selling, sharing, and trading data and data assets.

Application of Pocket mHealth as a tool for occupational health, presented in the Workshop on Personalized Health & Intelligent Workplaces Transforming Ergonomics ‘18 - Acknowledgement to EIT Health.

Lack of good and standardised Electronic Health Record (EHR) Graphical User Interfaces (GUI) can hinder the acceptance of ground-breaking medical devices devoted to healthcare professionals and / or patients.