Distinction in International Artificial Intelligence competition
A group of students and researchers from the Department of Informatics of the Athens University of Economics and Business and the Archimedes Unit of Athena RC won this year the first place in the international Artificial Intelligence competition "ImageCLEFmed Caption", a distinction that they have been systematically achieving for the last five years.
This is a competition in which research groups systems take part, using artificial intelligence, to automatically link medical images from X-rays, ultrasounds, CT and MRI scans, etc., with tags of medical concepts for the better management of large volumes of data, but also aiming to produce medical diagnosis texts.
The Natural Language Processing research group of the Athens University of Economics and Business, which took first place in the automatic assignment of medical labels (Concept Detection) and third place in the automatic description of medical images (Caption Prediction), includes the Professor of Artificial Intelligence at the Department of Informatics of the University of Economics of Athens (OPA) and collaborating researcher of the "Archimedes" Unit of the "Athena" Research Center, Ion Androutsopoulos, the researcher of the Department of Informatics of the OPA and the University of Stockholm, Yannis Pavlopoulos, the PhD candidate of the Department of Informatics of the OPA and a doctoral scholar of of the "Archimedes" Unit, Georgios Moschovis, the PhD candidate of the Department of Informatics of the OPA, Foivos Charalambakos, and the postgraduate student of the Master's Program "Computer Science" of the Department of Informatics of the OPA, Panagiotis Kaliosis.
The OPA team entered the competition with systems based on deep learning, a form of machine learning that uses deep artificial neural networks to encode and categorize images, as well as generate text, a technology also used by ChatGPT.
The team developed new forms of neural networks specifically for the competition, but also modified existing forms by combining different machine learning methods.