This subject, developed within the framework of the advanced studies in Biomedical Engineering, aims to train its students in the field of Artificial Intelligence applied to the conceptualization, design, and implementation of intelligent clinical decision support systems, understood and applied to both healthcare products and diagnostic services.
To this end, the teaching approach will prioritise, on the one hand, the understanding of the fundamental theoretical concepts underlying models of artificial intelligence, both those based on symbolic reasoning and those based on statistical learning, and, on the other hand, the practical realisation of these articulated models through the design and programming of the information flows of the corresponding algorithms.
The content will cover essential knowledge related to the concept of intelligent systems, exploring its meaning and variants, which will involve a methodological exploration of the inherent logics and guiding principles of the different inference processes, in order to subsequently comment on and develop the implementation of intelligent systems through different approaches, covering symbolic and statistical inference processes.
Due to the specific nature of the theoretical content of the subject, a gradual and progressive understanding, supported by hermeneutic debate, of the interpretation of propositional and first-order logic, of the concept of uncertainty and risk, of the bases of inference in learning techniques, of the distinction and applicability of the different paradigms of reasoning, of the importance in clinical decision-making of the predictive techniques of artificial intelligence and, in general, of the conceptual design of coherent, robust and reliable intelligent systems will be promoted.
All this is aimed at acquiring, understanding and applying the knowledge and cognitive resources necessary to develop the ability to create intelligent system schemes that can be translated into products and services in the biomedical sector, with a proven predictive and preventive capacity, and endowed with reasoning and decision-making abilities. At the end of the course, the student will be able to demonstrate the necessary theoretical and practical competence to create an intelligent product or service that solves a real complex problem in the field of biomedical engineering, which implies facing a problematic issue with a multiplicity of influencing variables, the permanent presence of uncertainty in its traditional variants, a relevant associated risk and, above all, the absence of a valid analytical, experimental or numerical model for its solution.
Finally, in addition to the skills and abilities already mentioned, the subject will include transversal training in data processing, programming fundamentals, the collection, analysis and presentation of clinical results and the development of proofs of concept, as well as other knowledge implicit in the study of intelligent systems.
