ArticleFrontiers in oncology2022
Two-Year Event-Free Survival Prediction in DLBCL Patients Based on
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence for Risk Stratification in Diffuse Large B-Cell Lymphoma: A Systematic Review of Classification Models and Predictive Performances.Medical sciences (Basel, Switzerland) · 2025Pooled it
- Machine learning enhances risk stratification and treatment failure prediction in diffuse large B-cell lymphoma.HemaSphere · 2026Article
- Automatic Lugano staging for risk stratification in lymphoma: a multicenter PET radiomics and machine learning study with survival analysis.Nuclear medicine communications · 2025Article
- An MRI-based radiomics nomogram to predict progression-free survival in patients with endometrial cancer.Future oncology (London, England) · 2025Article
- Comparison of conventional and radiomics-based analysis of myocardial infarction using multimodal non-linear optical microscopy.Scientific reports · 2025Article
- Clinician-driven automated data preprocessing in nuclear medicine AI environments.European journal of nuclear medicine and molecular imaging · 2025Article
- Comparative performance of multiple ensemble learning models for preoperative prediction of tumor deposits in rectal cancer based on MR imaging.Scientific reports · 2025Article
- Radiomics based onQuantitative imaging in medicine and surgery · 2025Article
- The Role of Artificial Intelligence and Radiomics in the Management of Lymphomas by PET/CT: The Clairvoyance in Clinic.Cancer management and research · 2025Review
- Review
- Clinical application ofJapanese journal of radiology · 2024Review
- Clinicopathological analysis of diffuse large B-cell lymphoma using molecular biomarkers: a retrospective analysis from 7 Hungarian centers.Frontiers in oncology · 2023Article
- Automated data preparation forFrontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: For the identification of high-risk patients in diffuse large B-cell lymphoma (DLBCL), we investigated the prognostic significance of Methods: Pre-treatment [ Results: The automated machine learning analysis of the Center 1 dataset revealed that the most important features for building 2-year EFS are as follows: max diameter, neighbor gray tone difference matrix (NGTDM) busyness, total lesion glycolysis, total metabolic tumor volume, and NGTDM coarseness. The predictive model built on the Center 1 dataset yielded 79% sensitivity, 83% specificity, 69% positive predictive value, 89% negative predictive value, and 0.85 AUC by evaluating the Center 2 dataset. Conclusion: Based on our dual-center retrospective analysis, predicting 2-year EFS built on imaging features is feasible by utilizing high-performance automated machine learning.
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