ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2022
Improved Prognosis of Treatment Failure in Cervical Cancer with Nontumor PET/CT Radiomics.
Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
18 citing papers in PubMed, 28 citations in OpenAlex.
- Article
- Radiomics and artificial intelligence in precision radiotherapy for cervical cancer: a narrative review.Frontiers in oncology · 2026Review
- Article
- Development and validation of the risk stratification based on deep learning and radiomics to predict survival of advanced cervical cancer.Scientific reports · 2025Article
- Habitat-based transformer model in pretreatmentBMC cancer · 2025Article
- Pre-Treatment PET Radiomics for Prediction of Disease-Free Survival in Cervical Cancer.Cancers · 2025Article
- Application of artificial intelligence in assisting treatment of gynecologic tumors: a systematic review.Visual computing for industry, biomedicine, and art · 2025Review
- Comparison of organ volumes and standardized uptake values in [18F]FDG-PET/CT images using MOOSE and TotalSegmentator to segment CT images.Medical physics · 2025Article
- Harnessing unsupervised machine learning with [Frontiers in oncology · 2025Article
- CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses.Journal of multidisciplinary healthcare · 2025Article
- Pretreatment Multi-sequence Contrast-Enhanced MRI to Predict Response to Immunotherapy in Unresectable Hepatocellular Carcinoma Using Transformer: A Multicenter Study.Journal of Cancer · 2025Article
- Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation.Cancer management and research · 2025Review
- Promising predictive molecular biomarkers for cervical cancer (Review).International journal of molecular medicine · 2024Review
- Impact ofJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- A common [18F]-FDG PET radiomic signature to predict survival in patients with HPV-induced cancers.European journal of nuclear medicine and molecular imaging · 2023Article
- Prediction of lymph node status in patients with early-stage cervical cancer based on radiomic features of magnetic resonance imaging (MRI) images.BMC medical imaging · 2023Article
- Recurrence risk stratification for locally advanced cervical cancer using multi-modality transformer network.Frontiers in oncology · 2023Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 1 institution in 1 country.
Funding
Abstract
Radiomics has been applied to predict recurrence in several disease sites, but current approaches are typically restricted to analyzing tumor features, neglecting nontumor information in the rest of the body. The purpose of this work was to develop and validate a model incorporating nontumor radiomics, including whole-body features, to predict treatment outcomes in patients with previously untreated locoregionally advanced cervical cancer.
Indexed as
Identifiers
What 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.