ResearcherInsermNo recent work listed
Valérie Paradis
Matched on ORCID iD 0000-0003-3142-3762; OpenAlex author ID A5055720674. Sources: ClinicalTrials.gov.
Their work
- Papers
- 8
- Trials
- 1 (principal investigator on 1)
- Grants
- 0
- Labs led
- 0
- Collaborators
- 33
2015: 1 paper · 2016: none · 2017: none · 2018: 1 paper · 2019: 3 papers · 2020: none · 2021: 1 paper · 2022: 1 paper, 1 trial · 2023: 1 paper
Papers 8
- Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma. Co-author DOI 10.1038/s41467-023-39026-y↗
- PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides Co-author DOI 10.1101/2022.01.04.474951↗
- Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features. Co-author DOI 10.3390/cancers13061234↗
- Inter- and intra-tumoural heterogeneity in cancer-associated fibroblasts of human pancreatic ductal adenocarcinoma. Co-author DOI 10.1002/path.5224↗
- Prognostic Biomarkers in Pancreatic Cancer: Avoiding Errata When Using the TCGA Dataset. Co-author DOI 10.3390/cancers11010126↗
- hENT1 Testing in Pancreatic Ductal Adenocarcinoma: Are We Ready? A Multimodal Evaluation of hENT1 Status. Co-author DOI 10.3390/cancers11111808↗
- In vitro, in vivo and ex vivo demonstration of the antitumoral role of hypocretin-1/orexin-A and almorexant in pancreatic ductal adenocarcinoma. Co-author DOI 10.18632/oncotarget.24084↗
- High c-Met expression in stage I-II pancreatic adenocarcinoma: proposal for an immunostaining scoring method and correlation with poor prognosis. Co-author DOI 10.1111/his.12691↗
Trials 1
- METabolic PROFILE of Hepatocarcinoma and Pancreatic Tumors Principal investigator NCT05794048↗
Closest collaborators
The 25 strongest of 33 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Jerome F. Cros · 8 shared papers, 2015–2023 · strength 0.72
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper Prognostic Biomarkers in Pancreatic Cancer: Avoiding Errata When Using the TCGA Dataset. DOI 10.3390/cancers11010126↗
- Rémy Nicolle · 5 shared papers, 2019–2023 · strength 0.53
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper Prognostic Biomarkers in Pancreatic Cancer: Avoiding Errata When Using the TCGA Dataset. DOI 10.3390/cancers11010126↗
- Pascal R. Hammel · 5 shared papers, 2015–2023 · strength 0.47
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features. DOI 10.3390/cancers13061234↗
- Jean‐Baptiste Bachet · 5 shared papers, 2015–2023 · strength 0.47
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features. DOI 10.3390/cancers13061234↗
- Magali Svrcek · 4 shared papers, 2019–2023 · strength 0.42
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features. DOI 10.3390/cancers13061234↗
- Vinciane Rebours · 4 shared papers, 2018–2023 · strength 0.42
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features. DOI 10.3390/cancers13061234↗
- Anne Couvelard Benveniste · 5 shared papers, 2015–2021 · strength 0.40
- Paper Prognostic Biomarkers in Pancreatic Cancer: Avoiding Errata When Using the TCGA Dataset. DOI 10.3390/cancers11010126↗
- Paper Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features. DOI 10.3390/cancers13061234↗
- Paper hENT1 Testing in Pancreatic Ductal Adenocarcinoma: Are We Ready? A Multimodal Evaluation of hENT1 Status. DOI 10.3390/cancers11111808↗
- Cindy Neuzillet · 4 shared papers, 2015–2023 · strength 0.36
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper Inter- and intra-tumoural heterogeneity in cancer-associated fibroblasts of human pancreatic ductal adenocarcinoma. DOI 10.1002/path.5224↗
- Louis de Mestier · 4 shared papers, 2015–2023 · strength 0.36
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Paper hENT1 Testing in Pancreatic Ductal Adenocarcinoma: Are We Ready? A Multimodal Evaluation of hENT1 Status. DOI 10.3390/cancers11111808↗
- Jérôme Raffenne · 3 shared papers, 2019–2021 · strength 0.28
- Paper Prognostic Biomarkers in Pancreatic Cancer: Avoiding Errata When Using the TCGA Dataset. DOI 10.3390/cancers11010126↗
- Paper Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features. DOI 10.3390/cancers13061234↗
- Paper hENT1 Testing in Pancreatic Ductal Adenocarcinoma: Are We Ready? A Multimodal Evaluation of hENT1 Status. DOI 10.3390/cancers11111808↗
- Charlie Saillard · 2 shared papers, 2022–2023 · strength 0.24
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Magali Richard · 2 shared papers, 2022–2023 · strength 0.24
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Juan Iovanna · 2 shared papers, 2022–2023 · strength 0.24
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Nelson Dusetti · 2 shared papers, 2022–2023 · strength 0.24
- Paper Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic… DOI 10.1038/s41467-023-39026-y↗
- Paper PACpAInt: a deep learning approach to identify molecular subtypes of pancreatic adenocarcinoma on histology slides DOI 10.1101/2022.01.04.474951↗
- Francesco Puleo · 2 shared papers, 2019–2021 · strength 0.18
- Annemilaï Tijeras‐Raballand · 2 shared papers, 2015–2019 · strength 0.12
- Philippe B Ruszniewski · 2 shared papers, 2015–2018 · strength 0.12
- Paper In vitro, in vivo and ex vivo demonstration of the antitumoral role of hypocretin-1/orexin-A and almorexant in pancreat… DOI 10.18632/oncotarget.24084↗
- Paper High c-Met expression in stage I-II pancreatic adenocarcinoma: proposal for an immunostaining scoring method and correl… DOI 10.1111/his.12691↗
- Alain Sauvanet Sauvanet · 2 shared papers, 2015–2018 · strength 0.12
- Paper In vitro, in vivo and ex vivo demonstration of the antitumoral role of hypocretin-1/orexin-A and almorexant in pancreat… DOI 10.18632/oncotarget.24084↗
- Paper High c-Met expression in stage I-II pancreatic adenocarcinoma: proposal for an immunostaining scoring method and correl… DOI 10.1111/his.12691↗
- Jérôme Torrisani · 1 shared paper, 2021 · strength 0.10
- Raphaël Maréchal · 1 shared paper, 2019 · strength 0.08
- Pierre Laurent‐Puig · 1 shared paper, 2019 · strength 0.08
- Anguraj Sadanandam · 1 shared paper, 2019 · strength 0.08
- Corinne Bousquet · 1 shared paper, 2019 · strength 0.08
- Mert Erkan · 1 shared paper, 2019 · strength 0.08
- Francesca Romana Delvecchio · 1 shared paper, 2019 · strength 0.08
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.