ArticleWorld journal of clinical cases2024
Computed tomography-based radiomics predicts the fibroblast-related gene
Article in World journal of clinical cases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Review
- Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice.Journal of translational medicine · 2025Article
- Radiomics and molecular analysis: Bridging the gap for predicting hepatocellular carcinoma prognosis.World journal of clinical cases · 2025Article
- Gene targets with therapeutic potential in hepatocellular carcinoma.World journal of gastrointestinal oncology · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHepatocellular carcinoma (HCC) is the most common subtype of liver cancer. The primary treatment strategies for HCC currently include liver transplantation and surgical resection. However, these methods often yield unsatisfactory outcomes, leading to a poor prognosis for many patients. This underscores the urgent need to identify and evaluate novel therapeutic targets that can improve the prognosis and survival rate of HCC patients.
aimTo construct a radiomics model that can accurately predict the
methodsGene expression, clinical parameters, HCC-related radiomics, and fibroblast-related genes were acquired from public databases. A gene model was developed, and its clinical efficacy was assessed statistically. Drug sensitivity analysis was conducted with identified hub genes. Radiomics features were extracted and machine learning algorithms were employed to generate a radiomics model related to the hub genes. A nomogram was used to illustrate the prognostic significance of the computed Radscore and the hub genes in the context of HCC patient outcomes.
results
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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.