Publications of Francesco Ciompi

2025

Papers in international journals

  1. M. D'Amato, J. van der Laak and F. Ciompi, "Weakly supervised regression enables interpretable tumor detection in whole-slide histopathology without negative cases", Scientific Reports, 2025;15.
    Abstract DOI PMID
  2. R. Lomans, V. Angerilli, J. Spronck, L. Kodach, I. Gullo, F. Carneiro, R. van der Post and F. Ciompi, "Deep learning for multiclass tumor cell detection in histopathology slides of hereditary diffuse gastric cancer", iScience, 2025;28:113064.
    DOI PMID
  3. M. Tran, P. Schmidle, R. Guo, S. Wagner, V. Koch, V. Lupperger, B. Novotny, D. Murphree, H. Hardway, M. D'Amato, J. Lefkes, D. Geijs, A. Feuchtinger, A. Böhner, R. Kaczmarczyk, T. Biedermann, A. Amir, A. Mooyaart, F. Ciompi, G. Litjens, C. Wang, N. Comfere, K. Eyerich, S. Braun, C. Marr and T. Peng, "Generating dermatopathology reports from gigapixel whole slide images with HistoGPT", Nature Communications, 2025;16.
    Abstract DOI PMID
  4. J.S. Bosma, K. Dercksen, L. Builtjes, R. André, C. Roest, S. Fransen, C. Noordman, M. Navarro-Padilla, J. Lefkes, N. Alves, M. de Grauw, L. van Eekelen, J. Spronck, M. Schuurmans, B. de Wilde, W. Hendrix, W. Aswolinskiy, A. Saha, J. Twilt, D. Geijs, J. Veltman, D. Yakar, M. de Rooij, F. Ciompi, A. Hering, J. Geerdink, H. Huisman, O. behalf of the consortium, M. de Grauw, L. van Eekelen, B. de Wilde, Q. van Lohuizen, M. Stegeman, K. Rutten, I. Smit, G. Stultiens, C. Overduin, M. Rutten, E. Scholten, R. van der Post, K. Grünberg, S. Vos, E. Taken, I. Nagtegaal, A. Mickan, M. Groeneveld, P. Gerke, J. Meakin, M. Looijen-Salamon, T. de Haas, F. Hoitsma, M. D'Amato and M. de Rooij, "The DRAGON benchmark for clinical NLP", npj Digital Medicine, 2025;8.
    Abstract DOI PMID
  5. T. Haddad, J. Bokhorst, L. van den Dobbelsteen, S. Öztürk, E. Baumann, S. van Vliet, K. Verrijp, N. Jamieson, C. Wood, M. Berger, R. Kirsch, M. Aben, N. Rutgers, H. Ueno, F. Ciompi, F. Simmer, J. van der Laak, A. Lugli, I. Zlobec and I. Nagtegaal, "Tumor budding and poorly differentiated clusters as a biological continuum in colorectal cancer invasion and prognosis", Scientific Reports, 2025;15.
    Abstract DOI PMID
  6. W. Aswolinskiy, R. van der Post, M. Campora, C. Baronchelli, L. Ardighieri, S. Vatrano, J. van der Laak, E. Munari, M. Simons, I. Nagtegaal and F. Ciompi, "Attention-Based Whole-Slide Image Compression Achieves Pathologist-Level Prescreening of Multiorgan Routine Histopathology Biopsies", Modern Pathology, 2025;38(11):100827.
    Abstract DOI

Preprints

  1. M. van Rijthoven, W. Aswolinskiy, L. Tessier, M. Balkenhol, J. Bogaerts, D. Drubay, L. Blesa, D. Peeters, E. Stovgaard, A. L\aenkholm , H. Haynes, L. Craciun, D. Larsimont, M. Amgad, L. Cooper, C. de Kock, V. Dechering, J. Lotz, N. Weiss, M. van Bockstal, C. Galant, E. Lips, H. Horlings, J. Wesseling, L. Mulder, S. van den Belt, K. Weber, P. Jank, C. Denkert, E. Munari, G. Bogina, C. Russ, A. Lemm, S. Loi, J. Douglas, S. Michiels, H. Joensuu, M. Fan, D. Lee, J. Ye, K. Byun, J. Kim, S. Xu, Z. Ji, F. Xie, J. Kuang, X. Chen, L. Chen, A. Tsakiroglou, R. Byers, M. Fergie, V. Ramanathan, A. Martel, A. Shephard, S. Ahmed Raza, M. Jahanifar, N. Rajpoot, S. Cho, D. Kim, H. Jang, C. Park, K. Kim, R. Donders, S. Maurits, M. Groeneveld, A. Mickan, J. Meakin, B. van Ginneken, R. Salgado, J. van der Laak and F. Ciompi, "Tumor-infiltrating lymphocytes in breast cancer through artificial intelligence: biomarker analysis from the results of the TIGER challenge", medRxiv, 2025.
    Abstract DOI
  2. C. Lems, L. Tessier, J. Bokhorst, M. van Rijthoven, W. Aswolinskiy, M. Pozzi, N. Klubickova, S. Dintzis, M. Campora, M. Balkenhol, P. Bult, J. Spronck, T. Detone, M. Barbareschi, E. Munari, G. Bogina, J. Wesseling, E. Lips, F. Ciompi, F. Meeuwsen and J. van der Laak, "A Multicentric Dataset for Training and Benchmarking Breast Cancer Segmentation in H&E Slides", arXiv:2510.02037, 2025.
    Abstract DOI arXiv

Papers in conference proceedings

  1. N. Khalili, J. Spronck, F. Ciompi, J. der Van Laak and G. Litjens, "A human-in-the-loop framework for refining deep learning models in pathology segmentation", Medical Imaging 2025: Digital and Computational Pathology, 2025:21.
    DOI
  2. C. Lems, N. Klubíčková, B. Brattoli, T. Lee, S. Kim, V. Besler, P. Fernandez, L. Pons, A. Laurinavicius, J. Drachneris, D. Montezuma, D. Oliveira, S. Vos, M. Balkenhol, J. van Ipenburg, A. Vos, M. Poceviciute, N. Khalili and F. Ciompi, "Towards a multicentric open DigitAL PatHology assIstant beNchmark: Initial Results from the DALPHIN Study", Laboratory Investigation, 2025;105:103609.
    DOI
  3. J. Lefkes, M. D'Amato, S. Sun, G. Litjens and F. Ciompi, "Large Language Models Automate Diagnostic Conclusions Generation from Microscopic Descriptions in Multiple Cancer Types", Laboratory Investigation, 2025;105:103608.
    DOI
  4. S. de Jong, A. Der Van Kroef, M. Groot, R. Verhoeven, E. Der Van Heijden and F. Ciompi, "AI-based benchmark to test the potential of 3-photon excited fluorescence in intraoperative lung cancer detection with multiphoton microscopy", European Respiratory Journal, 2025;66(suppl 69).
    Abstract DOI

PhD theses

  1. E. Markus-Smeets, "Build bridges to break barriers: Using quantitative imaging to understand pancreas tumor biology", PhD thesis, 2025.
    Abstract Url