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A Multimodal Dataset for Survival Prediction in Resected Pancreatic Ductal Adenocarcinoma

Research Medical/Healthcare AI

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TL;DR - Researchers released a multimodal dataset linking pancreatic cancer histology, clinical variables, targeted sequencing, and long-term survival outcomes for 302 resected PDAC patients. Initial benchmarks show clinical variables outperform image-only and neural multimodal models, providing a baseline for future externally validated survival prediction.

  • The dataset includes 446 H&E whole-slide images, clinicopathological data, survival outcomes, and targeted sequencing for 154 patients.
  • Ridge Cox regression achieved mean concordance of 0.649, rising slightly to 0.652 with KRAS and TP53 mutation status.
  • The image-only attention model achieved 0.603 concordance; multimodal fusion led the neural models at 0.619.
  • The retrospective, single-centre cohort requires external validation before broader clinical applicability can be established.

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A Multimodal Dataset for Survival Prediction in Resected Pancreatic Ductal Adenocarcinoma

arXiv cs.CV Anh-Tien Nguyen, Mawuko Tettey, Jacqueline Michelle Metsch, Teresa Zimmer, Niklas Ullrich, Mario Duker, Sandra Rungeling, Kirsten Reuter-Jessen, Tessa Rosenthal, Lena-Christin Conradi, Michael Ghadimi, Alexander Konig, Elisabeth Hessmann, Volker Ellenrieder, Philipp Strobel, Hanibal Bohnenberger, Anne-Christin Hauschild 2026-09-24 arXiv:2609.29726
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Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-26 14:13:32.250826 UTC

TL;DR - Researchers released a multimodal dataset linking pancreatic cancer histology, clinical variables, targeted sequencing, and long-term survival outcomes for 302 resected PDAC patients. Initial benchmarks show clinical variables outperform image-only and neural multimodal models, providing a baseline for future externally validated survival prediction.

  • The dataset includes 446 H&E whole-slide images, clinicopathological data, survival outcomes, and targeted sequencing for 154 patients.
  • Ridge Cox regression achieved mean concordance of 0.649, rising slightly to 0.652 with KRAS and TP53 mutation status.
  • The image-only attention model achieved 0.603 concordance; multimodal fusion led the neural models at 0.619.
  • The retrospective, single-centre cohort requires external validation before broader clinical applicability can be established.
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