Artificial intelligence, deep learning, machine learning, neural networks and others, are terms that have acquired extraordinary value in recent years. The extremely high computational power achieved today and that is constantly growing allows us to talk about artificial intelligence methods that surpass humans in many of the tasks that we have classically developed, no matter how complex they may be, and among them is medicine. All these advances have allowed us to speak of "Precision Medicine" in which big data and artificial intelligence techniques play an essential role. The evidence-based medicine that came to light about 50 years ago has been crucial in improving the quality of medical care in recent decades, but most commonly the evidence generated is applicable to general populations of patients with a very limited degree of adaptability to more specific patient profiles, not to mention the peculiarities of each particular patient. For this series of sessions, we have invited a select group of medical and engineering professionals of various nationalities. All of them are directly involved in this type of development that includes the use of various artificial intelligence methodologies on medical research and practice. Thus, they will present us the results of their investigations and those of other groups and their potential or real implications for clinical practice. From the centennial electrocardiogram, through multiple imaging techniques or cardiovascular hemodynamics, all these diagnostic approaches are susceptible to exploitation by these artificial intelligence methods, yielding unimaginable possibilities that will extraordinarily enhance the discriminative diagnostic power of the techniques and their therapeutic implications. All this towards a truly personalized evidence-based medical care.

Al inscribirse quedará aceptado para asistir al curso. El curso será impartido a través de la plataforma ZOOM. Les será enviado el Link de Acceso a la Plataforma el viernes 18/11/2022.

Se facilitará diploma de asistencia a los alumnos que acudan al 80% del curso.