Innovation in the treatment of infectious diseases

29 de April de 2024

At Cognodata, we face the pandemic with a clear vision: to develop a more scalable and resilient healthcare system. Through our collaboration with, we are advancing an innovative project that uses cutting-edge technology to improve healthcare processes through generative models that study infectious diseases.

Analysing the dynamics of infectious diseases

By building generative systems, we analyse the dynamics of infectious diseases under different conditions, which facilitates a more effective and adaptive response by health professionals.

Application of 4P Medicine

Our approach is guided by the principles of 4P medicine – predictive, personalised, preventive and participatory. It ensures that our project not only responds to current needs, but also anticipates and adapts to the future health conditions of each patient. It allows us to be more precise in our treatments, anticipating the evolution of diseases and adjusting treatments to the specific needs of each individual.

AI technologies and in-silico medicine

During the research project, we combined AI technologies and in-silico medicine in order to develop a pilot platform with advanced algorithms. With this, we simulate and treat specific diseases, through an iterative process of continuous improvement and validation to align with healthcare needs and maintain quality standards.

Using this approach allows us to make accurate analyses and predictions based on large volumes of data.  For example, a generative model that studies the spread of infections in pneumonia. This model predicts how infection spreads through the lungs and analyses the immune response, improving the understanding and treatment of disease.

Unlike current applications of machine learning in medicine, which are often experimental and work in a piecemeal fashion, our technology offers a fully integrated solution. It not only improves cohesion and patient experience, but also introduces advanced predictive models and dynamic disease simulations.

Development of Intelligent Adaptive Control System (IACS)

The research uses Schema-based Machine Learning (SBL) to model dynamic systems through networks of interconnected schemas, including sensors to measure aspects of the organism and actors for regulatory actions. In this way, we fuse multi-modal and multi-level information to improve patient care and diagnosis with precision, enabling personalisation of treatments.

Chest X-ray image comparing the findings of the algorithm with the markings made by the radiologists.

Adaptability of Cognodata technology

Thanks to the collaboration with, the adaptability of our technology to different approaches, such as segmentation and personalisation of treatment, represents a fundamental change in our vision to improve medicine. This technology integrates perfectly both in the Public Health System and in specialised entities, adjusting to the specific needs of each patient segment and taking advantage of different information formats.

From Cognodata we want to provide fundamental tools for medical decision making. These tools make it possible to attend to a greater number of patients efficiently and improve precision and prevention in diagnosis, prognosis and treatment. Achieving a fundamental step towards precision medicine.