ArticleJournal of hepatocellular carcinoma2021
Deep Learning-Based Prediction of Future Extrahepatic Metastasis and Macrovascular Invasion in Hepatocellular Carcinoma.
Article in Journal of hepatocellular carcinoma, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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
5 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Bibliometrics of artificial intelligence applications in hepatobiliary surgery from 2014 to 2024.World journal of gastrointestinal surgery · 2025Article
- Radiomics and machine learning based on preoperative MRI for predicting extrahepatic metastasis in hepatocellular carcinoma patients treated with transarterial chemoembolization.European journal of radiology open · 2024Article
- Efficacy and safety of regorafenib as second-line treatment for patients with hepatocellular carcinoma and macrovascular invasion and(or) extrahepatic metastasis.Journal of gastrointestinal oncology · 2023Article
- Technological Advancements in Interventional Oncology.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
17 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeFor timely treatment of extrahepatic metastasis and macrovascular invasion (aggressive progressive disease [PD]) in hepatocellular carcinoma, models aimed at stratifying the risks of subsequent aggressive PD should be constructed. PATIENTS AND
methodsAfter dividing 332 patients from five hospitals into training (n = 236) and validation (n = 96) datasets, non-invasive models, including clinical/semantic factors (Model
resultsAmong the constructed models, Model
conclusionOur deep learning-based model successfully stratified the risks of aggressive PD. In the high-risk population, current guideline indicates that first-line treatments are insufficient to prevent extrahepatic metastasis and macrovascular invasion and ensure survival benefits, so more therapies may be explored for these patients.
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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.