
MODEST: diagnosis and algorithms
MODEST is a program financed by 'European Union aimed at developing mathematical models to support medical diagnosis. Innovation and experience thus become synergistic assets at the service of the patient, strengthened by what machine learning is able to do starting from the previous diagnoses. MODEST immediately returned important results, with a sensitivity in the identification of atrial fibrillation equal to 81%.So the head Sebastian Sager explains what the experiment moves from:
We tried to to find mathematical models in the literature that accurately describe what is happening, but in the end we had to create our own. The second step was optimization, involving many different disciplines: mathematics, medicine, computer science, biology and machine learning.
Instruments of this type are able to multiply the accuracy of the diagnosis and, consequently, substantially improve the effectiveness of treatments. Much of the future of healthcare passes through projects of the caliber of MODEST (and the related funding), which today can sit on the shoulders of giants with tools and analytical skills that were unthinkable until just a few years ago.