ARTIFICIAL INTELLIGENCE FOR HEALTH
The production of health data from the care of patients in a medical environment but also through connected objects or large national databases has opened up the new concept of digital health, centred on the ability to use these big data in health. Simultaneously, the concept of One Health has emerged, in which patient health is no longer reduced to its purely medical dimension but also considers the elements of its ecological environment, as well as animal health. It promotes a multidisciplinary and integrative approach to health in order to meet the challenges of the increasing incidence of chronic diseases and the of emergence of infectious pathologies with pandemic risk. The tools of artificial intelligence, thanks to their ability to process large datasets originating from various source (medical, environmental, epidemiological...) and to establish a "medical meaning" to these data, have allowed the development of a wide field of applications, such as diagnostic aid, prediction, prevention or treatment of diseases, that have given its substance to the concept of precision medicine, and also strengthened the involvement of the patient who becomes an actor in his/her care, thanks to the real-time data that he/she can generate.
In this context, the purpose of the AI4OneHealth programme is to address the issue of Artificial Intelligence in Health in the context of swift changes in healthcare systems and the merging of novel approaches. It provides a broad multidisciplinary training in the emerging field of AI for Health
applied to the analysis and exploitation of data created during the treatment of the patients but also by the patients themselves or from large national databases. Methods of AI dedicated to analysis of health data, including text mining, neural network modelling, visualization and modelling, deep learning for precision medicine, give rise to major health, ethical and societal challenges.
The program offers the opportunity to gain the skills that will make you an expert in this new field, capable of understanding both the complexity of AI methods for analysis of health data and their practical application for the treatment of patients and for the expansion and the improvement of its strategies, based on the One Health concept.
AI4ONEHEALTH OFFERS A SOLID GROUNDING IN THE ARTIFICIAL INTELLIGENCE AND APPLIED COMPUTER SCIENCES THAT SUPPORT GLOBAL HEALTH
WHY THE AI4ONEHEALTH PROGRAMME?
The vision of AI4OneHealth is to provide international students with the education, tools and training to become competent and responsible health professionals. Our programme is designed to make the student understand and master solid scientific foundations, in order to take part in the growing area of Artificial Intelligence for Health.
We challenge ourselves to provide high standards in education and training, where the students’ best interests constitute the cornerstone of our values.
During the first semester, students attend online advanced courses. The second semester is dedicated to the Master thesis carried out within any academic or industrial laboratory. Université Grenoble Alpes and all the partners of the Multidisciplinary Institute in Artificial Intelligence (MIAI) of Grenoble provide opportunities for students to participate in research projects supervised by world-class scientists. Students will also have the opportunity to participate in two thematic schools that provide students with a unique opportunity to improve and apply their knowledge in IA through advanced classes and practical sessions while shaping and building their projects.
The first thematic school is dedicated to "learning from health data", and the second to innovation for precision medicine in oncology.
All in all, each student has to earn 60 ECTS credits (30 credits for each semester). Students will be requested to choose a number of compulsory elective subjects worth three or six credits each. The Master's programme is taught exclusively in English. Students are therefore required to be fluent in that language.
November 15: Opening of applications
To be determined: Closing of application
Notification of the selection results to selected students gradually from the end of April to mid-July
Mid-late September to January 15th: Semester 1 (online courses)
January 15th to July 31st (of year N+1): Internship (Master's thesis)