Paper · 34563443
Magnetic Resonance Radiomics and Machine-learning Models: An Approach for Evaluating Tumor-stroma Ratio in Patients with Pancreatic Ductal Adenocarcinoma.
Meng Y and 10 others. Acad Radiol, 2022. Cited by 18 papers, by iCite.
11 sourcespapers-2026-11-12-0.1.0
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ConductScience Library. Magnetic Resonance Radiomics and Machine-learning Models: An Approach for Evaluating Tumor-stroma Ratio in Patients with Pancreatic Ductal Adenocarcinoma. Papers, record 34563443. Release papers-2026-11-12-0.1.0, 12 Nov 2026. https://conductscience.org/library/papers/34563443
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Paper
PubMed's record of the paper, with iCite's citation figures. No abstract is shown.
- Title
- Magnetic Resonance Radiomics and Machine-learning Models: An Approach for Evaluating Tumor-stroma Ratio in Patients with Pancreatic Ductal Adenocarcinoma.
- PubMed
Topics7
NLM's MeSH indexing of the paper, its major topics first.
| MeSH term | Major |
|---|---|
| Carcinoma, Pancreatic Ductal | Major topic |
| Pancreatic Neoplasms | Major topic |
| Humans | |
| Machine Learning | |
| Magnetic Resonance Imaging | |
| Magnetic Resonance Spectroscopy | |
| Retrospective Studies |
Source PubMed
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Trials0
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Comments and corrections0
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References0
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Cited by12
The papers in our copy of PubMed whose reference list names this one, newest first. iCite, which reads more sources, counts 18 citations.
| PMID | Title | Journal | Year | In Papers | Source |
|---|---|---|---|---|---|
| 42,856,962 | Super-Resolution MRI-Derived Tumor-Stroma Ratio Phenotyping for Prognostic and Therapeutic Stratification in Pancreatic Ductal Adenocarcinoma. | MedComm (2020) | 2026 | https://conductscience.org/library/papers/42856962 | PubMed |
| 41,339,875 | AI-based neoadjuvant immunotherapy response prediction across pan-cancer: a comprehensive review. | Cancer Cell Int | 2025 | https://conductscience.org/library/papers/41339875 | PubMed |
| 41,226,014 | Advancing Prostate Cancer Assessment: A Biparametric MRI (T2WI and DWI/ADC)-Based Radiomic Approach to Predict Tumor-Stroma Ratio. | Diagnostics (Basel) | 2025 | https://conductscience.org/library/papers/41226014 | PubMed |
| 41,149,498 | Comparative Prognostic Roles of β-Catenin Expression and Tumor-Stroma Ratio in Pancreatic Cancer: Neoadjuvant Chemotherapy vs. Upfront Surgery. | Curr Oncol | 2025 | https://conductscience.org/library/papers/41149498 | PubMed |
| 41,049,608 | Noninvasive Computed Tomography-Based Quantification of Tumor Fibrosis Predicts Pancreatic Cancer Response to Gemcitabine/Nab-Paclitaxel. | Research (Wash D C) | 2025 | https://conductscience.org/library/papers/41049608 | PubMed |
| 41,013,373 | Nomogram for predicting tumor-stroma ratio in pancreatic ductal adenocarcinoma using dual-energy computed tomography. | BMC Med Imaging | 2025 | https://conductscience.org/library/papers/41013373 | PubMed |
| 40,770,286 | The development of a multimodal prediction model based on CT and MRI for the prognosis of pancreatic cancer. | BMC Gastroenterol | 2025 | https://conductscience.org/library/papers/40770286 | PubMed |
| 40,487,956 | Computed tomography-based deep learning radiomics model for preoperative prediction of tumor immune microenvironment in colorectal cancer. | World J Gastrointest Oncol | 2025 | https://conductscience.org/library/papers/40487956 | PubMed |
| 39,412,688 | One novel transfer learning-based CLIP model combined with self-attention mechanism for differentiating the tumor-stroma ratio in pancreatic ductal adenocarcinoma. | Radiol Med | 2024 | https://conductscience.org/library/papers/39412688 | PubMed |
| 39,118,942 | Dendritic cell vaccination combined with irreversible electroporation for treating pancreatic cancer-a narrative review. | Ann Transl Med | 2024 | https://conductscience.org/library/papers/39118942 | PubMed |
1 to 10 of 12
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None in this release.
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None in this release.
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- Trials
- 2026-11-12
- Gene search
- 2026-11-11
- Pipelines
- 2026-09-18
Sources 11
- ChEMBL, through Open TargetsCC BY-SA 3.0
- ClinicalTrials.govNo license stated
- HGNCCC0
- iCiteCC BY 4.0
- NCBI GenePublic domain (US government)
- NIH RePORTER's grant and paper linksPublic domain
- Open TargetsCC0 1.0
- PMC's ID filePublic domain (US government)
- PubMedNLM's terms
- PubTator 3Public domain
- UniProtCC BY 4.0
Each source's terms
- ChEMBL, through Open TargetsCC BY-SA 3.0, for the parts from ChEMBL. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
- ClinicalTrials.govnone stated
- HGNCCC0: https://www.genenames.org/about/license/
- iCiteCC BY 4.0
- NCBI GeneNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
- NIH RePORTER's grant and paper linksPublic domain (NIH RePORTER)
- Open TargetsCC0 1.0. Open Targets asks that users cite its latest paper: Buniello et al. 2025, Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery, Nucleic Acids Research 53(D1):D1467, PMID 39657122. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
- PMC's ID fileNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
- PubMedNLM's terms
- PubTator 3Public domain
- UniProtCC BY 4.0. UniProt's licence file: "All databases and documents in the UniProt FTP directory may be copied and redistributed freely, without advance permission, provided that this copyright statement is reproduced with each copy." UniProt asks that users cite its latest paper: The UniProt Consortium, UniProt: the Universal Protein Knowledgebase in 2025, Nucleic Acids Research 53:D609-D617, https://doi.org/10.1093/nar/gkae1010. Read on 9 Nov 2026 at https://www.uniprot.org/help/license
ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.
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