AI and the future of healthcare

Increasingly, artificial intelligence (AI) is helping us rewrite the future of our world. But in Spain, María Isabel Bernardos has already rewritten some of her own future, swapping a career in astrophysics for one as a data scientist at Capgemini Engineering.

We asked María about that career change, and how the AI project she is currently working on typifies the culture of innovation at Capgemini – and may lead to a healthier future for us all.

You’re a data scientist at Capgemini, but what did you do before that?

I came to Capgemini from the academic world. After finishing a PhD in astrophysics in 2020, I worked on research projects in the field of high-energy astrophysics, and my focus was always the data analysis and data science side of it. 

What inspired you to change careers and swap astrophysics and academia for a data science role at Capgemini?

Even when I worked in astrophysics, my daily work was oriented towards data science, applying machine learning techniques to the analysis of astronomical data. In the end, I realised that this is what I really wanted to do – but sadly, a profile like mine, more oriented to the technical parts of the analysis than to scientific publications, is not as valued in the academic world. Also, the lack of stability of the scientific career contributed to the change. Now, after almost a year, I think it has been for the better.

What is the AI project have you been working on with Capgemini?

It’s a project called Artificial Intelligence for Healthy Aging (AI4HA). The goal is to apply AI in the diagnosis and early treatment of diseases related to aging. The use of AI tools in healthcare is increasingly widespread, as it allows physicians to improve their diagnostic capacities, detect rare diseases earlier, and then make the best choice of treatments. We are using AI to follow the health of individuals over time, to be able to predict when these diseases will start to appear, and when to start early treatment to prevent the disease or its symptoms.

How might this project make a difference to our world?

As populations grow older, the health of elderly people will increasingly weigh on our public healthcare services. Conducting a large study of the evolution of diseases over time, and looking at how we can detect them earlier, would require following patients’ health over several stages of their life. This is often an unaffordable task for public healthcare services. But with AI and the use of predictive models, we can speed up this task and alleviate the burden on healthcare services.

What happens next with the project?

We’ve already collected a large amount of data from patients that is now being used to train the AI models – and even to develop wearable devices that could monitor patients’ progress. We have also been working on an online platform, where partners will be able to retrieve results and explanations for specific forecasts in a graphical, user-friendly environment. The next steps will be to discuss each partner’s specific needs and to tailor the solutions accordingly.

It all sounds very exciting, but what is it really like to work on projects such as this?

It makes me feel like my work is contributing to creating a better world and a better society, as we are using the technology and all our knowledge to improve people’s lives. The most exciting part of it is having the opportunity to research the latest advances in AI. Every day I’m learning new ways to upgrade my skills and about the many ways we can apply AI to healthcare.

In such a cutting-edge field, there must be challenges. What are they?

One of the main challenges is the proper treatment of data, because it is delicate, personal information about the health conditions of real people. We have to be careful and respectful with the treatment of the data, following strict protocols. Also, medicine is a very complex and wide field, which means there are a lot of uncertainties. Forecasting diseases that develop over time can be affected by many factors, which is a big challenge for data scientists.

What are the skills you need to succeed in these types of roles?

For me, one of the most important skills is efficient problem solving. You face challenges every day that you have probably never encountered before. Having the ability to break down those problems and come up with original and efficient solutions is the only way to avoid being stalled. Results are not always as you expect; difficulties arise and modifications need to be made, so you need to adapt your solutions to the new conditions to get the best results.

When you are pursuing cutting-edge solutions, there is no marked path. You have to take all the state-of-the-art knowledge of the field you are studying and then create something new. It’s very stimulating and satisfying.

Can you sum up a culture or philosophy of innovation at Capgemini?

It’s about being innovative, original, and creative. You can’t stay in your safe space. It’s about pushing forward and looking for new ways to do things. To do that you need to be curious and not afraid to propose ideas and try new things, even if they don’t work in the end. The path to innovation is built upon trial and error, approaches that initially do not work, but that eventually lead to solutions to people’s problems. And, of course, helping people get older in good health, in full fitness, without disease, is one way for us all to have a better future. That’s really the Capgemini promise of helping people get the future they want.