Computational & Translational Pathology Lab
Publications
72 found
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van den Berg, Nikki et al. (2026) ‘Deep Learning-Based Screening for POLE mutations on Histopathology Slides in Endometrial Cancer’, medRxiv [Preprint]. (medRxiv). Available at: https://doi.org/10.64898/2026.02.06.26345335.
van den Berg, Nikki et al. (2026) ‘Deep Learning-Based Screening for POLE mutations on Histopathology Slides in Endometrial Cancer’, medRxiv [Preprint]. (medRxiv). Available at: https://doi.org/10.64898/2026.02.06.26345335.
Bräutigam, Konstantin et al. (2026) ‘Integrating artificial intelligence ( AI ) into colorectal cancer reporting’, Journal of Pathology [Preprint]. Available at: https://doi.org/10.1002/path.70029.
Bräutigam, Konstantin et al. (2026) ‘Integrating artificial intelligence ( AI ) into colorectal cancer reporting’, Journal of Pathology [Preprint]. Available at: https://doi.org/10.1002/path.70029.
Chen, Boqi et al. (2026) ‘Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology’, in Lecture Notes in Computer Science. Cham: Springer Science and Business Media Deutschland GmbH (Lecture Notes in Computer Science), pp. 554–564. Available at: https://doi.org/10.1007/978-3-032-04978-0_53.
Chen, Boqi et al. (2026) ‘Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology’, in Lecture Notes in Computer Science. Cham: Springer Science and Business Media Deutschland GmbH (Lecture Notes in Computer Science), pp. 554–564. Available at: https://doi.org/10.1007/978-3-032-04978-0_53.
Gosztonyi, Benedict et al. (2026) ‘Safety of Multi-Omics–Guided Therapy in Advanced Melanoma: A Matched Comparative Cohort Analysis’, JCO Precision Oncology, 10(1). Available at: https://doi.org/10.1200/po-25-00896.
Gosztonyi, Benedict et al. (2026) ‘Safety of Multi-Omics–Guided Therapy in Advanced Melanoma: A Matched Comparative Cohort Analysis’, JCO Precision Oncology, 10(1). Available at: https://doi.org/10.1200/po-25-00896.
Pnev, S. et al. (2026) ‘Scheduled Cross-Domain Multi-center DINO for Robust High-Content Screening Representation Learning’, in Lecture Notes in Computer Science. Cham: Springer Science and Business Media Deutschland GmbH (Lecture Notes in Computer Science), pp. 432–441. Available at: https://doi.org/10.1007/978-3-032-09513-8_42.
Pnev, S. et al. (2026) ‘Scheduled Cross-Domain Multi-center DINO for Robust High-Content Screening Representation Learning’, in Lecture Notes in Computer Science. Cham: Springer Science and Business Media Deutschland GmbH (Lecture Notes in Computer Science), pp. 432–441. Available at: https://doi.org/10.1007/978-3-032-09513-8_42.
Frei, Céline Arlette et al. (2025) ‘The chromatin guardian ATRX is a strong prognostic biomarker in melanoma’, Scientific Reports, 16(1). Available at: https://doi.org/10.1038/s41598-025-30842-4.
Frei, Céline Arlette et al. (2025) ‘The chromatin guardian ATRX is a strong prognostic biomarker in melanoma’, Scientific Reports, 16(1). Available at: https://doi.org/10.1038/s41598-025-30842-4.
Mehra, Tarun et al. (2025) ‘Comparative cost analysis of a diagnostic multi-omics platform for decision support in advanced cancer – results from the Tumor Profiler Melanoma project’, npj Precision Oncology, 10(1). Available at: https://doi.org/10.1038/s41698-025-01229-5.
Mehra, Tarun et al. (2025) ‘Comparative cost analysis of a diagnostic multi-omics platform for decision support in advanced cancer – results from the Tumor Profiler Melanoma project’, npj Precision Oncology, 10(1). Available at: https://doi.org/10.1038/s41698-025-01229-5.
Sakalauskaite, Gabriele et al. (2025) ‘A BioID-based approach uncovers the interactome of hexose-6-phosphate dehydrogenase in breast cancer cells and identifies anterior gradient protein 2 as an interacting partner’, Cell and Bioscience, 15(1). Available at: https://doi.org/10.1186/s13578-025-01388-9.
Sakalauskaite, Gabriele et al. (2025) ‘A BioID-based approach uncovers the interactome of hexose-6-phosphate dehydrogenase in breast cancer cells and identifies anterior gradient protein 2 as an interacting partner’, Cell and Bioscience, 15(1). Available at: https://doi.org/10.1186/s13578-025-01388-9.
Shin, JaeWoong et al. (2025) ‘OCELOT 2023: Cell detection from cell–tissue interaction challenge’, Medical Image Analysis. 07.08.2025, 106. Available at: https://doi.org/10.1016/j.media.2025.103751.
Shin, JaeWoong et al. (2025) ‘OCELOT 2023: Cell detection from cell–tissue interaction challenge’, Medical Image Analysis. 07.08.2025, 106. Available at: https://doi.org/10.1016/j.media.2025.103751.
Schmid, Dominic et al. (2025) ‘Tumor immune dynamics and long-term clinical outcome of stage IIIA NSCLC patients treated with neoadjuvant chemoimmunotherapy’, Nature Communications, 16(1). Available at: https://doi.org/10.1038/s41467-025-63696-5.
Schmid, Dominic et al. (2025) ‘Tumor immune dynamics and long-term clinical outcome of stage IIIA NSCLC patients treated with neoadjuvant chemoimmunotherapy’, Nature Communications, 16(1). Available at: https://doi.org/10.1038/s41467-025-63696-5.
Nonchev, K. et al. (2025) ‘DeepSpot2Cell: Predicting Virtual Single-Cell Spatial Transcriptomics from H&E images using Spot-Level Supervision’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2025.09.23.678121.
Nonchev, K. et al. (2025) ‘DeepSpot2Cell: Predicting Virtual Single-Cell Spatial Transcriptomics from H&E images using Spot-Level Supervision’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2025.09.23.678121.
Wiesmann, F. et al. (2025) ‘RIPPLET: Mutation-Only Gene and Pathway Profiling for Precision Oncology’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2025.09.17.676675.
Wiesmann, F. et al. (2025) ‘RIPPLET: Mutation-Only Gene and Pathway Profiling for Precision Oncology’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2025.09.17.676675.
Fusi, Irene et al. (2025) ‘PD-1–targeted cis-delivery of an IL-2 variant induces a multifaceted antitumoral T cell response in human lung cancer’, Science Translational Medicine, 17(816). Available at: https://doi.org/10.1126/scitranslmed.adr3718.
Fusi, Irene et al. (2025) ‘PD-1–targeted cis-delivery of an IL-2 variant induces a multifaceted antitumoral T cell response in human lung cancer’, Science Translational Medicine, 17(816). Available at: https://doi.org/10.1126/scitranslmed.adr3718.
Zajac, N. et al. (2025) ‘Comparison of single-cell long-read and short-read transcriptome sequencing via cDNA molecule matching: quality evaluation of the MAS-ISO-seq approach’, 7. Available at: https://doi.org/10.1093/nargab/lqaf089.
Zajac, N. et al. (2025) ‘Comparison of single-cell long-read and short-read transcriptome sequencing via cDNA molecule matching: quality evaluation of the MAS-ISO-seq approach’, 7. Available at: https://doi.org/10.1093/nargab/lqaf089.
Bräutigam, Konstantin et al. (2025) ‘Spatially resolved analysis of TGF/BMP signalling in pancreatic ductal adenocarcinoma by digital pathology identifies patient subgroups with adverse outcome’, BMC Cancer, 25(1). Available at: https://doi.org/10.1186/s12885-025-14751-3.
Bräutigam, Konstantin et al. (2025) ‘Spatially resolved analysis of TGF/BMP signalling in pancreatic ductal adenocarcinoma by digital pathology identifies patient subgroups with adverse outcome’, BMC Cancer, 25(1). Available at: https://doi.org/10.1186/s12885-025-14751-3.
Andani, Sonali et al. (2025) ‘Histopathology-based protein multiplex generation using deep learning’, Nature Machine Intelligence, 7(8), pp. 1292–1307. Available at: https://doi.org/10.1038/s42256-025-01074-y.
Andani, Sonali et al. (2025) ‘Histopathology-based protein multiplex generation using deep learning’, Nature Machine Intelligence, 7(8), pp. 1292–1307. Available at: https://doi.org/10.1038/s42256-025-01074-y.
Litchfield, Cassandra et al. (2025) ‘Integrating Formalin-Fixed, Paraffin-Embedded–Derived Whole-Genome Sequencing into Routine Molecular Pathology: Validation and First Experiences in Metastatic Melanoma’, Journal of Molecular Diagnostics, 27, pp. 722–735. Available at: https://doi.org/10.1016/j.jmoldx.2025.04.011.
Litchfield, Cassandra et al. (2025) ‘Integrating Formalin-Fixed, Paraffin-Embedded–Derived Whole-Genome Sequencing into Routine Molecular Pathology: Validation and First Experiences in Metastatic Melanoma’, Journal of Molecular Diagnostics, 27, pp. 722–735. Available at: https://doi.org/10.1016/j.jmoldx.2025.04.011.
Schoenpflug, Lydia A. et al. (2025) ‘Navigating real-world challenges: A case study on federated learning in computational pathology’, Journal of Pathology Informatics, 18. Available at: https://doi.org/10.1016/j.jpi.2025.100464.
Schoenpflug, Lydia A. et al. (2025) ‘Navigating real-world challenges: A case study on federated learning in computational pathology’, Journal of Pathology Informatics, 18. Available at: https://doi.org/10.1016/j.jpi.2025.100464.
Berg, I., Wu, J. and Koelzer, V.H. (2025) ‘Generative cerebral vasculature visualization using spatial transcriptomic data’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2025.07.10.664153.
Berg, I., Wu, J. and Koelzer, V.H. (2025) ‘Generative cerebral vasculature visualization using spatial transcriptomic data’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2025.07.10.664153.
Miglino, Nicola et al. (2025) ‘Feasibility of multiomics tumor profiling for guiding treatment of melanoma’, Nature Medicine, 31, pp. 2430–2441. Available at: https://doi.org/10.1038/s41591-025-03715-6.
Miglino, Nicola et al. (2025) ‘Feasibility of multiomics tumor profiling for guiding treatment of melanoma’, Nature Medicine, 31, pp. 2430–2441. Available at: https://doi.org/10.1038/s41591-025-03715-6.
Rubin, David T et al. (2025) ‘Deployment of an Artificial Intelligence Histology Tool to Aid Qualitative Assessment of Histopathology Using the Nancy Histopathology Index in Ulcerative Colitis’, Inflammatory Bowel Diseases, 31(6), pp. 1630–1636. Available at: https://doi.org/10.1093/ibd/izae204.
Rubin, David T et al. (2025) ‘Deployment of an Artificial Intelligence Histology Tool to Aid Qualitative Assessment of Histopathology Using the Nancy Histopathology Index in Ulcerative Colitis’, Inflammatory Bowel Diseases, 31(6), pp. 1630–1636. Available at: https://doi.org/10.1093/ibd/izae204.
Karakulak, T. et al. (2025) ‘Heterogeneous and novel transcript expression in single cells of patient-derived clear cell renal cell carcinoma organoids’, 35. Available at: https://doi.org/10.1101/gr.279345.124.
Karakulak, T. et al. (2025) ‘Heterogeneous and novel transcript expression in single cells of patient-derived clear cell renal cell carcinoma organoids’, 35. Available at: https://doi.org/10.1101/gr.279345.124.
Nonchev, Kalin et al. (2025) ‘DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images’, in Neural Information Processing Systems (NeurIPS). Mexico: Cold Spring Harbor Laboratory (Neural Information Processing Systems (NeurIPS)), pp. 1–10. Available at: https://doi.org/10.1101/2025.02.09.25321567.
Nonchev, Kalin et al. (2025) ‘DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images’, in Neural Information Processing Systems (NeurIPS). Mexico: Cold Spring Harbor Laboratory (Neural Information Processing Systems (NeurIPS)), pp. 1–10. Available at: https://doi.org/10.1101/2025.02.09.25321567.
Schoenpflug, Lydia A et al. (2025) ‘Tumour purity assessment with deep learning in colorectal cancer and impact on molecular analysis’, Journal of Pathology, 265(2), pp. 184–197. Available at: https://doi.org/10.1002/path.6376.
Schoenpflug, Lydia A et al. (2025) ‘Tumour purity assessment with deep learning in colorectal cancer and impact on molecular analysis’, Journal of Pathology, 265(2), pp. 184–197. Available at: https://doi.org/10.1002/path.6376.
Palles, Claire et al. (2025) ‘Comparison between germline and somatic loss-of-function RNF43 mutations reveals different genotype-phenotype associations and provides insights into the genetic mechanisms of colorectal tumourigenesis’, Gut [Preprint]. 24.12.2025. Available at: https://doi.org/10.1136/gutjnl-2025-337030.
Palles, Claire et al. (2025) ‘Comparison between germline and somatic loss-of-function RNF43 mutations reveals different genotype-phenotype associations and provides insights into the genetic mechanisms of colorectal tumourigenesis’, Gut [Preprint]. 24.12.2025. Available at: https://doi.org/10.1136/gutjnl-2025-337030.
Wu,Jiqing, Berg,Ingrid and Koezler,Viktor H. (2025) ‘Generative cerebral vasculature visualization using spatial transcriptomic data’, bioRxiv (Cold Spring Harbor Laboratory) [Preprint].
Wu,Jiqing, Berg,Ingrid and Koezler,Viktor H. (2025) ‘Generative cerebral vasculature visualization using spatial transcriptomic data’, bioRxiv (Cold Spring Harbor Laboratory) [Preprint].
Wu,Jiqing et al. (2025) ‘Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion’, arXiv (Cornell University) [Preprint].
Wu,Jiqing et al. (2025) ‘Tera-MIND: Tera-scale mouse brain simulation via spatial mRNA-guided diffusion’, arXiv (Cornell University) [Preprint].
Vledder, Annegé et al. (2024) ‘B cells critical for outcome in high grade serous ovarian carcinoma’, International Journal of Cancer, 155(12), pp. 2265–2276. Available at: https://doi.org/10.1002/ijc.35149.
Vledder, Annegé et al. (2024) ‘B cells critical for outcome in high grade serous ovarian carcinoma’, International Journal of Cancer, 155(12), pp. 2265–2276. Available at: https://doi.org/10.1002/ijc.35149.
Eerkens, Anneke L. et al. (2024) ‘Neoadjuvant immune checkpoint blockade in women with mismatch repair deficient endometrial cancer: a phase I study’, Nature Communications , 15(1). Available at: https://doi.org/10.1038/s41467-024-52098-8.
Eerkens, Anneke L. et al. (2024) ‘Neoadjuvant immune checkpoint blockade in women with mismatch repair deficient endometrial cancer: a phase I study’, Nature Communications , 15(1). Available at: https://doi.org/10.1038/s41467-024-52098-8.
Fan, Fan et al. (2024) ‘CohortFinder: an open-source tool for data-driven partitioning of digital pathology and imaging cohorts to yield robust machine-learning models’, npj Imaging, 2(1). Available at: https://doi.org/10.1038/s44303-024-00018-2.
Fan, Fan et al. (2024) ‘CohortFinder: an open-source tool for data-driven partitioning of digital pathology and imaging cohorts to yield robust machine-learning models’, npj Imaging, 2(1). Available at: https://doi.org/10.1038/s44303-024-00018-2.
Lafarge, Maxime W. et al. (2024) ‘Image-based consensus molecular subtyping in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy’, npj Precision Oncology, 8(1). Available at: https://doi.org/10.1038/s41698-024-00580-3.
Lafarge, Maxime W. et al. (2024) ‘Image-based consensus molecular subtyping in rectal cancer biopsies and response to neoadjuvant chemoradiotherapy’, npj Precision Oncology, 8(1). Available at: https://doi.org/10.1038/s41698-024-00580-3.
Schoenpflug, Lydia A. et al. (2024) ‘A review on federated learning in computational pathology’, Computational and Structural Biotechnology Journal, 23, pp. 3938–3945. Available at: https://doi.org/10.1016/j.csbj.2024.10.037.
Schoenpflug, Lydia A. et al. (2024) ‘A review on federated learning in computational pathology’, Computational and Structural Biotechnology Journal, 23, pp. 3938–3945. Available at: https://doi.org/10.1016/j.csbj.2024.10.037.
Wegmann, Rebekka et al. (2024) ‘Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia’, Nature Communications , 15(1). Available at: https://doi.org/10.1038/s41467-024-53535-4.
Wegmann, Rebekka et al. (2024) ‘Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia’, Nature Communications , 15(1). Available at: https://doi.org/10.1038/s41467-024-53535-4.
Wu, Jiqing and Koelzer, Viktor H. (2024) ‘Towards generative digital twins in biomedical research’, Computational and Structural Biotechnology Journal, 23, pp. 3481–3488. Available at: https://doi.org/10.1016/j.csbj.2024.09.030.
Wu, Jiqing and Koelzer, Viktor H. (2024) ‘Towards generative digital twins in biomedical research’, Computational and Structural Biotechnology Journal, 23, pp. 3481–3488. Available at: https://doi.org/10.1016/j.csbj.2024.09.030.
Wu, Jiqing and Koelzer, Viktor H. (2024) ‘Towards generative digital twins in biomedical research’, Computational and Structural Biotechnology Journal, 23, pp. 3481–3488. Available at: https://doi.org/10.1016/j.csbj.2024.09.030.
Wu, Jiqing and Koelzer, Viktor H. (2024) ‘Towards generative digital twins in biomedical research’, Computational and Structural Biotechnology Journal, 23, pp. 3481–3488. Available at: https://doi.org/10.1016/j.csbj.2024.09.030.
Sobottka, Bettina et al. (2024) ‘Immune Phenotype-Genotype Associations in Primary Clear Cell Renal Cell Carcinoma and Matched Metastatic Tissue’, Modern Pathology, 37(10). Available at: https://doi.org/10.1016/j.modpat.2024.100558.
Sobottka, Bettina et al. (2024) ‘Immune Phenotype-Genotype Associations in Primary Clear Cell Renal Cell Carcinoma and Matched Metastatic Tissue’, Modern Pathology, 37(10). Available at: https://doi.org/10.1016/j.modpat.2024.100558.
Roth, Lilian et al. (2024) ‘CD8 + T-cells restrict the development of peritoneal metastasis and support the efficacy of hyperthermic intraperitoneal chemotherapy (HIPEC)’, Scientific Reports, 14(1). Available at: https://doi.org/10.1038/s41598-024-72826-w.
Roth, Lilian et al. (2024) ‘CD8 + T-cells restrict the development of peritoneal metastasis and support the efficacy of hyperthermic intraperitoneal chemotherapy (HIPEC)’, Scientific Reports, 14(1). Available at: https://doi.org/10.1038/s41598-024-72826-w.
Nowak, Marta et al. (2024) ‘Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer’, Cell Reports Medicine, 5(9). Available at: https://doi.org/10.1016/j.xcrm.2024.101727.
Nowak, Marta et al. (2024) ‘Single-cell AI-based detection and prognostic and predictive value of DNA mismatch repair deficiency in colorectal cancer’, Cell Reports Medicine, 5(9). Available at: https://doi.org/10.1016/j.xcrm.2024.101727.
Huellner, M.W. et al. (2024) ‘Distinct [18F]FDG-PET imaging features of a newly recognized and yet uncharacterized RDD-ECD overlap disease entity’, European Journal of Nuclear Medicine and Molecular Imaging, 51(11), pp. 3465–3466. Available at: https://doi.org/10.1007/s00259-024-06751-5.
Huellner, M.W. et al. (2024) ‘Distinct [18F]FDG-PET imaging features of a newly recognized and yet uncharacterized RDD-ECD overlap disease entity’, European Journal of Nuclear Medicine and Molecular Imaging, 51(11), pp. 3465–3466. Available at: https://doi.org/10.1007/s00259-024-06751-5.
Wu, Jiqing and Koelzer, Viktor H. (2024) ‘GILEA: In silico phenome profiling and editing using GAN Inversion’, Computers in Biology and Medicine, 179. Available at: https://doi.org/10.1016/j.compbiomed.2024.108825.
Wu, Jiqing and Koelzer, Viktor H. (2024) ‘GILEA: In silico phenome profiling and editing using GAN Inversion’, Computers in Biology and Medicine, 179. Available at: https://doi.org/10.1016/j.compbiomed.2024.108825.
Domingo, Enric et al. (2024) ‘Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors’, eBioMedicine. 16.07.2024, 106. Available at: https://doi.org/10.1016/j.ebiom.2024.105228.
Domingo, Enric et al. (2024) ‘Identification and validation of a machine learning model of complete response to radiation in rectal cancer reveals immune infiltrate and TGFβ as key predictors’, eBioMedicine. 16.07.2024, 106. Available at: https://doi.org/10.1016/j.ebiom.2024.105228.
Immer, Alexander et al. (2024) ‘Probabilistic pathway-based multimodal factor analysis’, Bioinformatics, 40(Supplement_1), pp. i189–i198. Available at: https://doi.org/10.1093/bioinformatics/btae216.
Immer, Alexander et al. (2024) ‘Probabilistic pathway-based multimodal factor analysis’, Bioinformatics, 40(Supplement_1), pp. i189–i198. Available at: https://doi.org/10.1093/bioinformatics/btae216.
Janowczyk, Andrew et al. (2024) ‘Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology’, Virchows Archiv, 485(1), pp. 13–30. Available at: https://doi.org/10.1007/s00428-023-03712-5.
Janowczyk, Andrew et al. (2024) ‘Swiss digital pathology recommendations: results from a Delphi process conducted by the Swiss Digital Pathology Consortium of the Swiss Society of Pathology’, Virchows Archiv, 485(1), pp. 13–30. Available at: https://doi.org/10.1007/s00428-023-03712-5.
Mahmood, Umair et al. (2024) ‘Stratification to Neoadjuvant Radiotherapy in Rectal Cancer by Regimen and Transcriptional Signatures’, Cancer Research Communications, 4(7), pp. 1765–1776. Available at: https://doi.org/10.1158/2767-9764.crc-23-0502.
Mahmood, Umair et al. (2024) ‘Stratification to Neoadjuvant Radiotherapy in Rectal Cancer by Regimen and Transcriptional Signatures’, Cancer Research Communications, 4(7), pp. 1765–1776. Available at: https://doi.org/10.1158/2767-9764.crc-23-0502.
Mahmood ,Umair et al. (2024) ‘Stratification to Neoadjuvant Radiotherapy in Rectal Cancer by Regimen and Transcriptional Signatures’, Cancer Research Communications, 4(7), pp. 1765–1776. Available at: https://doi.org/10.1158/2767-9764.CRC-23-0502.
Mahmood ,Umair et al. (2024) ‘Stratification to Neoadjuvant Radiotherapy in Rectal Cancer by Regimen and Transcriptional Signatures’, Cancer Research Communications, 4(7), pp. 1765–1776. Available at: https://doi.org/10.1158/2767-9764.CRC-23-0502.
Volinsky-Fremond, Sarah et al. (2024) ‘Author Correction: Prediction of recurrence risk in endometrial cancer with multimodal deep learning (Nature Medicine, (2024), 30, 7, (1962-1973), 10.1038/s41591-024-02993-w)’, Nature Medicine, 30(7), p. 2092. Available at: https://doi.org/10.1038/s41591-024-03126-z.
Volinsky-Fremond, Sarah et al. (2024) ‘Author Correction: Prediction of recurrence risk in endometrial cancer with multimodal deep learning (Nature Medicine, (2024), 30, 7, (1962-1973), 10.1038/s41591-024-02993-w)’, Nature Medicine, 30(7), p. 2092. Available at: https://doi.org/10.1038/s41591-024-03126-z.
Volinsky-Fremond, Sarah et al. (2024) ‘Prediction of recurrence risk in endometrial cancer with multimodal deep learning’, Nature Medicine, 30(7), pp. 1962–1973. Available at: https://doi.org/10.1038/s41591-024-02993-w.
Volinsky-Fremond, Sarah et al. (2024) ‘Prediction of recurrence risk in endometrial cancer with multimodal deep learning’, Nature Medicine, 30(7), pp. 1962–1973. Available at: https://doi.org/10.1038/s41591-024-02993-w.
Domingo, Enric et al. (2024) ‘Prognostic and Predictive Value of Immunoscore in Stage III Colorectal Cancer: Pooled Analysis of Cases From the SCOT and IDEA-HORG Studies’, Journal of Clinical Oncology. 14.03.2024, 42(18), pp. 2207–2218. Available at: https://doi.org/10.1200/jco.23.01648.
Domingo, Enric et al. (2024) ‘Prognostic and Predictive Value of Immunoscore in Stage III Colorectal Cancer: Pooled Analysis of Cases From the SCOT and IDEA-HORG Studies’, Journal of Clinical Oncology. 14.03.2024, 42(18), pp. 2207–2218. Available at: https://doi.org/10.1200/jco.23.01648.
Malla, Sudhir B. et al. (2024) ‘Correction to: Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer (Nature Genetics, (2024), 56, 3, (458-472), 10.1038/s41588-024-01654-5)’, Nature Genetics, 56(6), p. 1321. Available at: https://doi.org/10.1038/s41588-024-01809-4.
Malla, Sudhir B. et al. (2024) ‘Correction to: Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer (Nature Genetics, (2024), 56, 3, (458-472), 10.1038/s41588-024-01654-5)’, Nature Genetics, 56(6), p. 1321. Available at: https://doi.org/10.1038/s41588-024-01809-4.
Wakkerman, Famke C et al. (2024) ‘Prognostic impact and causality of age on oncological outcomes in women with endometrial cancer: a multimethod analysis of the randomised PORTEC-1, PORTEC-2, and PORTEC-3 trials’, The Lancet Oncology, 25(6), pp. 779–789. Available at: https://doi.org/10.1016/s1470-2045(24)00142-6.
Wakkerman, Famke C et al. (2024) ‘Prognostic impact and causality of age on oncological outcomes in women with endometrial cancer: a multimethod analysis of the randomised PORTEC-1, PORTEC-2, and PORTEC-3 trials’, The Lancet Oncology, 25(6), pp. 779–789. Available at: https://doi.org/10.1016/s1470-2045(24)00142-6.
Aubreville, Marc et al. (2024) ‘Domain generalization across tumor types, laboratories, and species — Insights from the 2022 edition of the Mitosis Domain Generalization Challenge’, Medical Image Analysis, 94. Available at: https://doi.org/10.1016/j.media.2024.103155.
Aubreville, Marc et al. (2024) ‘Domain generalization across tumor types, laboratories, and species — Insights from the 2022 edition of the Mitosis Domain Generalization Challenge’, Medical Image Analysis, 94. Available at: https://doi.org/10.1016/j.media.2024.103155.
Zajac, N. et al. (2024) ‘Comparison of Single-cell Long-read and Short-read Transcriptome Sequencing of Patient-derived Organoid Cells of ccRCC: Quality Evaluation of the MAS-ISO-seq Approach’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2024.03.14.584953.
Zajac, N. et al. (2024) ‘Comparison of Single-cell Long-read and Short-read Transcriptome Sequencing of Patient-derived Organoid Cells of ccRCC: Quality Evaluation of the MAS-ISO-seq Approach’. Cold Spring Harbor Laboratory. Available at: https://doi.org/10.1101/2024.03.14.584953.
Malla, Sudhir B. et al. (2024) ‘Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer’, Nature Genetics, 56(3), pp. 458–472. Available at: https://doi.org/10.1038/s41588-024-01654-5.
Malla, Sudhir B. et al. (2024) ‘Pathway level subtyping identifies a slow-cycling biological phenotype associated with poor clinical outcomes in colorectal cancer’, Nature Genetics, 56(3), pp. 458–472. Available at: https://doi.org/10.1038/s41588-024-01654-5.
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