Our second guest in the Fifth seminar D2 series has been Chiara Marzi, a postdoctoral research fellow of the Institute of Applied Physics “Nello Carrara” – National Research Council CNR. She talked about the topic of Artificial Intelligence in Neuroimaging, explaining how applying AI techniques to life sciences data can enhance the accuracy in pinpointing biomarkers or biological markers, which are the measurable indicators for medical states. In particular, professor Marzi showed how if Machine Learning is applied to neuroimaging, it can help find hidden patterns among data, combining statistical and mathematical tools to achieve early diagnosis. For example, Magnetic Resonance Imaging of the brain can be studied through fractal analysis, in order to find morphological changes due to healthy ageing or neurological disease, with the aim of identifying it before its symptoms.

As we tried to learn more about it, we had the chance of asking her a couple of questions.

Professor Marzi, how Big Data and Artificial Intelligence are applied to your field? 

In medicine and especially in medical imaging, big data combined with artificial intelligence have huge potential. The first results are certainly encouraging. On the one hand, collecting a large amount of medical data is not easy. However, the effort could be rewarded by more accurate and general results. Artificial intelligence, then, is fundamental in analyzing large amounts of data and could lead to the discovery of new biomarkers, able to perform early diagnosis and monitoring of treatments and rehabilitation.

Would you help us understand the outlook and future development of your research and how it will improve diagnostic quality?

Prospectively, I hope that more and more high-quality medical data will be shared and made available to the entire scientific community. Thus scientists could develop new artificial intelligence methods and algorithms on them. In this way, all branches of medicine will benefit, aiming at personalized pathways from diagnosis to treatment.

More information about Chiara Marzi and her research can be found on her personal page.

You can access the recording of this and all other seminars at this link. (Registration needed)