Representation of PJATK Gdańsk at the ML in PL 2024 conference

Strong representation of PJATK Gdańsk at the conference ML in EN 2024! Our lecturer Barbara Klaudel and Computer Science student Kacper Knitter talked about the use of AI in medicine using the UMIE datasets project as an example. This is the largest publicly available collection of labeled medical imaging data , containing more than one million images from 20 open datasets. The project unifies a variety of medical data formats (including X-ray, CT and MRI) through a standardized processing pipeline and mapping to the RadLex ontology. The project aims to lay the groundwork for the development of more advanced AI models in the field of medical imaging.

Meanwhile, Computer Science student Maciej Gierczak, graduate student Kinga Marszalkowska and our lecturer Alexander Obuchowski presented the Aesculap model In the poster session. Aesculap is a Polish open-source model designed for secure integration with hospital infrastructure , which is designed to address data privacy and model control issues. The model was built on Bielik-v2 and trained on a variety of medical sources, including 800,000 synthetic medical instructions. The project aims to support Polish health care by supporting medical records and clinical decision making , while maintaining the highest standards of privacy and stability.