Innovation and health have always gone hand in hand. Nowadays we have the privilege of being able to access countless technological developments and innovative healthcare, but for the vast majority of our existence none of this existed. My generation, for example, doesn't know what a world is like without antibiotics, dentists or an X-ray. But even though these tools are now so commonplace, there is a lot of room to conquer in terms of improving people's lives and health, not least because there are always new diseases challenging medicine and there is an increasing need to optimise healthcare so that responses become faster and more efficient.

It is for all these reasons that technological innovation in health is an ever-accelerating reality, with Artificial Intelligence (AI) coming up more frequently nowadays and its weight becoming increasingly significant in clinical practice. Nádia Búgia

That said, I've decided to identify 5 areas where the advances of AI in healthcare are being felt the most:

Robotic assistance: Surgeries performed remotely are now a reality thanks to remote-controlled robots, achieving the same level of precision, reducing recovery times and enabling access to specialists anywhere on the planet. Another great achievement of robotic assistance is chatbots used to monitor mental health symptoms, provide emotional support and detect warning situations that lead to referrals to specialised services.

Operational efficiency: AI systems have revolutionised the operational ecosystem in that they optimise hospital management and work processes, act in terms of patient and healthcare unit data security and reduce operating costs. Imaging is also seeing major developments with algorithm systems that interpret medical images in order to identify diseases and irregularities.

Data management: AI analyses data at a speed and acuity unattainable by any human. With this technology, genetic data and individual characteristics can be analysed in order to apply tailor-made treatments to each patient. AI-assisted diagnosis has been widely used to help doctors diagnose when there is a large amount of clinical data that needs to be interconnected quickly and accurately, just as in pharmacology data analysis tools are relevant to the discovery of new drugs and therapies.

Monitoring and preventive diagnosis: Long-range technologies make it possible to monitor patients from a distance, facilitating ongoing monitoring of chronic diseases and preventive action by reading signals that allow early detection of health problems. Still from a preventative perspective, Artificial Intelligence algorithms also work in our favour by being able to identify disease patterns and risks through the collection of patient data. Scale and accessibility: We mustn't forget that it takes many years from the moment a scientific discovery is made until it is applied. Therefore, in line with what has already been mentioned, the faster the research and the more efficient the tests and their correlations, the quicker the therapies will be applied to patients. So it's only natural that AI is now a viable driver of faster solutions, thus hastening the scalability of the solution so that access can be extended to the general population.

In fact, I consider myself lucky to live in a world where healthcare is brutally developed compared to my grandparents' time and with the prospect of more and more technological advances aimed at prolonging and improving our lives. There's no doubt that we live in exciting times.