The Institute of Health Research La Fe (IIS La Fe) is working on a project called COVID-19 face to face in order to anticipate the number of infections and know their evolution as well as to the demand for health services in order to optimize the management of health care resources.
According to the centre’s statement, this project will serve to “create care and logistics solutions, based on data sciencethat can be used immediately in the fight against Covid-19″.
The project is led by the Joint Research Unit on Information and Communication Technologies Applied to the Reengineering of Socio-Sanitary Processes of the IIS La Fe, which directs the Dr. Bernardo ValdiviesoIt has also had the participation of partners such as the Instituto Tecnológico de Informática (ITI), the Instituto Valenciano de Inteligencia Artificial of the UPV and the company Lucentia of the University of Alicante.
It has also been selected by the Valencian Agency for Innovation (AVI) to receive funding from a grant from the Generalitat Valenciana (Covid-19-SCI).
As reported by IIS La Fe, this tool “proposes the study, development, and evaluation of different predictive and descriptive models on Covid-19 that allow the analysis and probabilistic estimation of the evolution, treatment and hospital management as well as the comparison of the impact evolution of Covid-19 in relation to other places and times”.
The objective, as they have indicated, is to identify possible risk factors that are associated with differences in the affectation, evolution and outcome of the infection in different individuals, in addition to “developing and adapting the machine learning tools currently available to improve the diagnosis and prognosis of the disease”.
The ultimate goal is to anticipate the number of infections and their severity, i.e. to anticipate the diagnosis and to know in advance the evolution of the disease.
The massive analysis of clinical data from patients and healthy populations, as explained by the IIS La Fe, “will make possible the development of predictive tools capable of predicting the clinical evolution of each patient, personalizing the lines of treatment, optimizing the management of care resources, identifying risk factors, recognizing new symptoms or clinical signs, as well as improving the care and preventive response”.
According to the doctor in charge of the project, Bernardo ValdiviesoIn the words of the report, “predicting the evolution and impact of the epidemic is fundamental to decision making. The analysis of massive data using Big Data and artificial intelligence techniques will enable early detection of the disease, as well as of serious complications associated with Covid-19. It will also allow the development and implementation of tools that facilitate the prediction of the resources needed to face the pandemic.
Healthy and Disgnosed Patients
By studying both healthy and diagnosed patients, predictive models will be developed for all disease states that can “predict a person’s chances of incubation, hospitalization, severe manifestations, those that may lead to ICU with or without possible use of respirators and those most likely to die.
In all these cases, probabilistic predictive models of the condition will be made, but also temporary predictive models of onset and duration that will help in the follow-up and monitoring of the patients’ clinical responses. This monitoring will not only allow the identification of new symptoms and clinical signs in the population, but also risk factors for contagion in health professionals.
The project also contemplates the study of the variables that have the greatest impact on clinical evolution. Thus, models will be developed to analyze the success of treatments administered to patients diagnosed with Covid-19 and will be used to identify new treatments. With all this information, predictive models of health service demand will be developed in order to optimize the management of health care resources.
The initiative came about as a result of the discussions of a multidisciplinary working group of clinicians and data scientists promoted by the regional secretary of Universities and Research, Carmen Beviato “encourage the combined work of experts in artificial intelligence and data science, health and emergency response representatives”.
With this multidisciplinary project, the IIS La Fe has stated that it seeks to “improve scientific evidence and the management of the current health crisis by integrating advanced statistical techniques and artificial intelligence into clinical care practice”.
