Archimedes NLP Theme and AUEB NLP Group at 89th Thessaloniki International Fair: Spotlight talk
Dates
2025-09-13 18:00 - 18:30
Venue
Thessaloniki International Fair, Thessaloniki, Greece
Speaker: Georgios Moschovis, Academic Fellow at Archimedes, Athena Research Center, Greece, and PhD at the Athens University of Economics and Business (AUEB), Greece
Title: "An Image speaks a Thousand Words (in Medicine as well)"
Room: Ioannis Vellidis Convention Center (Leof. Stratou 3, Thessaloniki, Greece), Stand 7 Amphitheater (Ground Floor), General Secretariat for Research and Innovation, Hellenic Ministry of Development at the 89th Thessaloniki International Fair, Thessaloniki, Greece
Abstract: We present the methods developed by Archimedes/AUEB NLP Group for medical image tagging, as well as automatically generating a diagnostic text from a set of medical images. Towards this objective, the first step is concept detection, which boils down to predicting the relevant concepts (tags) for medical images, whereas the end goal is caption generation. This demo is based on the best approaches developed by Archimedes/AUEB NLP Group during its participation in the 9th edition of the ImageCLEFmedical Caption (concept Detection and Caption Prediction subtasks), but also as part of our collaboration with the Echocardiography Lab of the "Papageorgiou" general hospital in Thessaloniki. More information can be found in this document.
Useful Links:
Title: "An Image speaks a Thousand Words (in Medicine as well)"
Room: Ioannis Vellidis Convention Center (Leof. Stratou 3, Thessaloniki, Greece), Stand 7 Amphitheater (Ground Floor), General Secretariat for Research and Innovation, Hellenic Ministry of Development at the 89th Thessaloniki International Fair, Thessaloniki, Greece
Abstract: We present the methods developed by Archimedes/AUEB NLP Group for medical image tagging, as well as automatically generating a diagnostic text from a set of medical images. Towards this objective, the first step is concept detection, which boils down to predicting the relevant concepts (tags) for medical images, whereas the end goal is caption generation. This demo is based on the best approaches developed by Archimedes/AUEB NLP Group during its participation in the 9th edition of the ImageCLEFmedical Caption (concept Detection and Caption Prediction subtasks), but also as part of our collaboration with the Echocardiography Lab of the "Papageorgiou" general hospital in Thessaloniki. More information can be found in this document.
Useful Links:
The paper from our participation in the 8th edition of ImageCLEF medical can be found here. Detailed information about our group can be found on its website. To see more about our work in medical imaging specifically, see also this announcement (in Greek) from AUEB, and this announcement (in English) from Archimedes/ΑthenaRC.
Disclaimer:
Disclaimer:
Please note that our systems are tools to aid medical professionals complete their diagnostic pipeline in an increased throughput and are prone to error. By no means our AI systems aim to replace medical doctors and radiologists.
