ArticleMolecular imaging and biology2021
Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [
Article in Molecular imaging and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and meta-analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck squamous cell carcinoma patients.Cancer medicine · 2023Pooled it
- Article
- Predicting aggressive disease and poor outcome in endometrial cancer using preoperative [European journal of nuclear medicine and molecular imaging · 2025Article
- An MRI-based radiomics nomogram to predict progression-free survival in patients with endometrial cancer.Future oncology (London, England) · 2025Article
- Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [Japanese journal of radiology · 2025Article
- Artificial intelligence radiomics in the diagnosis, treatment, and prognosis of gynecological cancer: a literature review.Translational cancer research · 2025Review
- Applying deep learning-based ensemble model to [Japanese journal of radiology · 2025Article
- Machine learning approach usingJapanese journal of radiology · 2024Article
- Clinical application ofJapanese journal of radiology · 2024Review
- Retrospective analysis of theRadiation oncology (London, England) · 2023Article
- Methodological evaluation of original articles on radiomics and machine learning for outcome prediction based on positron emission tomography (PET).Nuklearmedizin. Nuclear medicine · 2023Review
- PrognosticDiagnostics (Basel, Switzerland) · 2023Article
- Application of Machine Learning Analyses Using Clinical and [Molecular imaging and biology · 2023Article
- An ultrasound-based radiomics model for survival prediction in patients with endometrial cancer.Journal of medical ultrasonics (2001) · 2023Article
- Article
- The usefulness of machine-learning-based evaluation of clinical and pretreatmentThe British journal of radiology · 2023Article
- The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [Molecular imaging and biology · 2023Article
- Prognostic analysis of curatively resected pancreatic cancer using harmonized positron emission tomography radiomic features.European journal of hybrid imaging · 2023Article
- Article
- Advances in Radiomics Research for Endometrial Cancer: A Comprehensive Review.Journal of Cancer · 2023Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo examine the prognostic significance of pretreatment 2-deoxy-2-[ PROCEDURES: Included in this retrospective study were 53 patients with endometrial cancers who underwent [
resultsThe five best predictors of disease progression were coarseness, gray-level run length nonuniformity, stage, treatment method, and gray-level zone length nonuniformity. The kNN model obtained the best performance classifier for predicting the disease progression (AUC =0.890, accuracy =0.849, F1 score =0.848, precision =0.857, and recall =0.849). Coarseness which was the first ranked radiomic feature was selected for survival analyses, and only coarseness remained as a significant and independent factor for both PFS (hazard ratios (HR), 0.65; 95 % confidence interval [CI], 0.49-0.86; p=0.003) and OS (HR, 0.52; 95 % CI, 0.36-0.76; p<0.001) at multivariate Cox regression analysis.
conclusions[
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33763816What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.