Utilisateur:Guaiana Thomas/Brouillon
[1]A long time ago, shamans were reading the future in their dreams, using their environment and the present to shape the future. As Prof.
Elias Zerhouni said “What will exist tomorrow in the medical field already exists today”. The Artificial Intelligence is a good example of that. Already in the 50’s, Alan Turing, who can be deemed as one of the fathers of AI, started questioning machine intelligence; but only recently, thanks to the empowerment of the GPU, it became a reality. It is now feasible to predict Alzheimer’s disease 6 years in advance! The beauty of MR imaging is that we are still far from the full expression of the predictive power for all the existing or future sequences. The next major steps in MR scan will be standardization and quantitative imaging. For instance, having reliable and repeatable absolute values is mandatory to diagnose a tumor in an automatic way, predict and follow its response to treatment.
Thirty years ago, when a trauma was arriving in an emergency room, only few images were
acquired. Now, around 5000 images are produced. Who can read them all in the context of an
emergency? No one. No one? Not really. AI can do it. Dr Peter Chang, head of the AI laboratory of
the University of California, Irvine (UCI), has developed an automatic triage of patients in neuro
emergencies based on CT scan. The first major AI applications in the medical field will be for CT
scan. Indeed, the Hounsfield unit standardizes its values.
For major vendors, healthcare reimbursements are one of the driving forces for the creation of research applications. However, hundreds of new start-ups are taking up the challenges left behind by the big companies which are focused on revenue only. They are leading the development of artificial pancreas, artificial heart, predictive diagnosis, genomic therapy, etc.
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- (en) Fayçal Djeridane, « Fayçal Djeridane Medical Innovation Improved » (consulté le )