The use of AI in tomorrow’s medicine
Big data” has become a major challenge in building the medicine of tomorrow. The advent of Omics, which are techniques for generating massive data (pioneered by genomics, but now complemented by other disciplines such as proteomics, metabolomics, lipidomics and transcriptomics), has led to the accumulation of a vast amount of heterogeneous data that represents a real treasure trove for research. But we still need to be able to use them. Omics have now been joined by another equally valuable form of data: patient health data. Scientific and technological advances have made it possible to produce and store data to create vast cohorts.
The challenge of Big Data today is to be able to structure, characterise, annotate and store this data in compliance with current regulations on the protection of personal data, so that it can be made accessible to research teams for use and thus contribute to the scientific progress of tomorrow.
The ICAN IHU and the challenge of AI in health
This fast-growing field has led to changes in regulations, requiring investigators, IT and legal teams to work closely together.IHU ICAN has risen to the challenge and set up a data expertise group. At the heart of this working group’s concerns are anticipating the needs of researchers, providing information to patients and sharing know-how at an international level. Drawing inspiration from structures in other fields (notably industry and agriculture), ICAN is exploring the hypotheses of data and service platforms for healthcare solutions in a number of areas : diagnosis of atrial fibrillation, management of NASH, management of diabetic foot, etc.
Finally, through its Board of Directors, ICAN is sharing its experience of the use of mass patient data with regulators, thereby contributing to regulatory developments in the field.
AI and megadata conference at the Conseil d’Etat
On Friday 10 February 2023, the ICAN IHU, together with the Conseil d’Etat, the CNIL and the Alliance IHU France, organised a major conference on the use of data and artificial intelligence (AI) in the healthcare sector. Watch the replay below.
Part 1
Part 2
The strengths of the IHU ICAN
Through large-scale innovative projects, ICAN is positioning itself as the leader in cardiometabolic health data.
MAESTRIA: a bold, innovative project on an international scale to build the medicine of tomorrow
The MAESTRIA (Machine Learning and Artificial Intelligence for Early Detection of Stroke and Atrial Fibrillation)research project aims to develop a new approach to early detection of atrial cardiomyopathy by creating multiparametric digital tools based on a new generation of biomarkers, in particular medical imaging associated with artificial intelligence, with the aim of meeting the major challenges of data integration and personalised medicine focused on atrial cardiomyopathy, atrial fibrillation and stroke.
By combining imaging data with physiological data (omics, clinical data, etc.) from patients, this platform will be able to identify new therapeutic targets to achieve improved diagnostic accuracy and increase the effectiveness and efficiency of treatments by enabling better prevention of complications of atrial cardiomyopathy, such as atrial fibrillation and stroke.
