Poster presentation at Helmholtz AI Conference 2025: AI for Science

(HAICON25 Poster) Multi-center Collaboration for Improved Lymph Node Metastasis Detection in Pancreatic Ductal Adenocarcinoma

Date
Jun 3, 2025 — Jun 5, 2025
Location
Karlsruhe, Germany

From 3–5 June 2025, David attended the Helmholtz AI Conference 2025 (“HAICON25”) at Messe Karlsruhe, Germany. The Helmholtz AI Conference 2025: AI for Science brought together over 600 researchers, industry practitioners, and students from across Europe to explore cutting-edge applications of artificial intelligence in the sciences—featuring inspiring keynotes, focused sessions, poster, and interactive networking events.'

Over three days of full-track sessions, I had the opportunity to present and discuss our work on Multi-center Collaboration for Improved Lymph Node Metastasis Detection in Pancreatic Ductal Adenocarcinoma. Expanding our previous, with the new retrospective multicenter cohort of 652 PDAC patients (391 with lymph node metastases; 59.97 %), we incorporated two additional German data sources; University Medicine Berlin (BER) and University Medical Center Göttingen (GÖT), providing a more rigorous testbed for our two-stage deep learning framework.

While these results underscore the power of combining automated segmentation priors with clinical features for enhanced LNM detection, the center-specific variability also reinforces the necessity of external validation and domain-adaptation strategies to ensure robust, generalizable performance before clinical deployment.

David also engaged in interactive formats such as the AI World Café, and the Pitch & Networking Event, and gain new perspectives from other disciplines which sparked cross-disciplinary interest. Overall, HAICON25 provided an valuable forum for exchanging ideas with peers in both academic and industrial AI, and for exploring new partnerships that will drive our research forward. I am already looking forward to next year’s meeting, and to applying the insights gained toward our ongoing projects in medical imaging and beyond. – David

David D. Gaviria
David D. Gaviria
PhD Candidate

David is currently a PhD candidate supervised by Prof. Dr. Shadi Albarqouni. He earned his master’s degree in AI from FIB, which is a joint program of UPC, UB, and URV. In 2019, he achieved the top spot in the SIIM-ISIC competition for skin lesion classification and has published his work at VISAPP 2023. David has a keen interest in utilizing technology for the betterment of society and intends to make contributions to AI in the field of medicine through his work at Albarqouni Lab.

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