The area of artificial intelligence (AI) has witnessed a significant revolution in recent years. In the field of biomedicine, it is leading to thousands of initiatives that now cover the entire spectrum of health interventions, from diagnostic processes to treatment monitoring, hospital organisation and health education, among others.
AI collects, classifies, organises and rationalises information. The aim is to identify patterns, relate concepts and draw conclusions from massive amounts of data that are impossible for the human brain to process. The use of AI algorithms helps to analyse large amounts of information in a short period of time and progress much faster when it comes to understanding diseases, thereby reducing research times. Conducting experiments until now had taken many years.
AI is capable of extracting patterns that can help medical professionals in areas such as diagnosis, treatment and follow-up. And trained AI can learn to identify the common parameters of a given disease, which helps to improve diagnostic skills and select the most appropriate therapy in each case, thus increasing the effectiveness of treatments. It is also being used as a tool to enhance disease prevention and early detection. It facilitates the monitoring and care of patients, surgical robotics, the discovery of new drugs, or even the training experience of professionals by simulating clinical situations so that medical staff can be exposed to these and learn without any risks.
In this debate, Alfonso Valencia, Natalia Pérez de la Ossa and Rodrigo Menchaca will discuss the present and future of applying AI in the field of biomedicine. They will talk about the great value of AI in developing algorithms that can predict the risk of suffering specific pathologies, new tools to support professionals in medical decision-making and the opportunities provided by AI in the field of healthcare training, among other topics.
Issues to be addressed include: The extent to which AI can improve disease diagnosis accuracy compared to traditional methods? What are the current limitations in the ability of AI to make accurate diagnoses? To what extent can AI predict the onset of diseases before they manifest themselves clinically? What are the ethical limits in collecting and using health data to develop AI algorithms? How to ensure the transparency of the AI algorithms used in medical decision-making?
The group led by Dr Alfonso Valencia applies machine learning and AI to personalised medicine. It co-leads a project that aims to identify new biomarkers for predicting the risk of relapse in acute lymphoblastic leukaemia. The team led by Dr Natalia Pérez de la Ossa is developing a new application geared towards a pre-hospital environment that employs artificial intelligence algorithms to help categorise stroke patients quickly and improve their chances of recovery. Rodrigo Menchaca is one of the founders of the AIS Channel, an initiative that encompasses two subjects, surgery and education. It is a digital platform that allows any doctor or surgeon to learn how to proceed in an intervention.
Speakers:
-
Alfonso Valencia, ICREA Professor, director of the Life Sciences Department at the Barcelona Supercomputing Centre (BSC-CNS).
-
Natalia Pérez de la Ossa, coordinator of the Stroke Unit at Hospital Germans Trias i Pujol and researcher at IGTP.
-
Rodrigo Menchaca, founding partner and advisor at AIS Channel and global director of digital skin at ISDIN.
Moderator:
-
Josep Corbella, journalist from La Vanguardia specialized in science and health.
Projects supported by CaixaResearch:
