BIGMED

In healthcare, modern technological tools (e.g., smartphones, connected watches, apps, etc.) are sources of an enormous amount of information. Indeed, with the emergence of e-health, massive data raises technical challenges concerning its storage and exploitation possibilities. The collection, cross-referencing and analysis of massive data (or Big Data) have, for some years now, been described as major issues in the health sciences.

Faced with the explosion in the use of digital technology in patient care, Big Data offers a response to the exploitation of this unstructured or, on the contrary, multi-structured data. The role of big data will then be to collect and manage databases in order to facilitate their storage and access.

This exploitation of data represents a real interest in the analysis, processing but also understanding of the occurrence of pathology/disease via the cross-referencing of healthcare data (mostly from heterogeneous sources): identification of factors, diagnostic or decision-making aid in the choice of appropriate and longitudinal patient follow-up, multiparametric analyses correlating clinical data from sensors with data in clinical research and the medical community, etc.

In order to exploit these immense volumes of raw, heterogeneous data, we need to turn to the new data sciences.

Making the most of Big Data requires sophisticated vector-based analyses and the implementation of mathematical algorithms. This scientific approach is in line with the concept of 4P medicine, i.e. Predictive and Preventive (acting in anticipation and therefore before the onset of symptoms and/or factors), Personalized and Participatory (adapting interventions and treatments to individual characteristics).

This is the key to the success of our business.