ReviewJournal of gastrointestinal cancer2020
Radiomics in Hepatocellular Carcinoma.
Review in Journal of gastrointestinal cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- AI-Driven Radiomics Assisted Prognostic Modeling for Hepatocellular Carcinoma with Portal Vein Invasion: A Retrospective Study.Biomedicines · 2026Article
- Integrating pretreatment CT radiomics and circulating tumor cells using machine learning to predict survival in hepatocellular carcinoma.Frontiers in pharmacology · 2026Article
- Correlation between dual-time-pointQuantitative imaging in medicine and surgery · 2025Article
- Prediction of microvascular invasion in hepatocellular carcinoma patients with MRI radiomics based on susceptibility weighted imaging and T2-weighted imaging.La Radiologia medica · 2024Article
- Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma: A quantitative review with Radiomics Quality Score.World journal of gastroenterology · 2024Review
- Machine learning with multimodal data for COVID-19.Heliyon · 2023Review
- An update on radiomics techniques in primary liver cancers.Infectious agents and cancer · 2022Article
- Morphological, dynamic and functional characteristics of liver pseudolesions and benign lesions.La Radiologia medica · 2022Review
- Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma.Infectious agents and cancer · 2021Review
- Progress of MRI Radiomics in Hepatocellular Carcinoma.Frontiers in oncology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRadiomics is an emerging field that extracts high-throughput imaging data from different types of images to build models and predict clinical outcomes ina non-invasive manner. This field currently is in the initial growth phase and lacks standardized evaluation criteria but remains a very promising tool for the future todevelop suitable biomarkers for diagnosis, prognosis, and treatment response assessments. The analysis of hepatocellular carcinoma by radiomics will contribute toearly diagnosis and treatment of tumors and improve survival and cure rates.
aimHerein, we aimed to provide an up-to-date overview of the principles of radiomics specifically regarding hepatocellular carcinoma (HCC) and discuss the current challenges and future advancements of radiomics for HCC.
Indexed as
Identifiers
32844349What 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.