ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2024
[A deep learning model based on magnetic resonance imaging and clinical feature fusion for predicting preoperative cytokeratin 19 status in hepatocellular carcinoma].
Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Radiomics and Deep Learning as Important Techniques of Artificial Intelligence - Diagnosing Perspectives in Cytokeratin 19 Positive Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2025Review
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Authors and funding
5 authors.
Funding
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Abstract
objectiveTo establish a deep learning model for testing the feasibility of combining magnetic resonance imaging (MRI) deep learning features with clinical features for preoperative prediction of cytokeratin 19 (CK19) status of hepatocellular carcinoma (HCC).
methodsA retrospective experiment was conducted based on the data of 116 HCC patients with confirmed CK19 status. A single sequence multi-scale feature fusion deep learning model (MSFF-IResnet) and a multi-scale and multimodality feature fusion model (MMFF-IResnet) were established based on the hepatobiliary phase (HBP), diffusion weighted imaging (DWI) sequences of enhanced MRI images, and the clinical features significantly correlated with CK19 status. The classification performance of the models were evaluated to assess the effectiveness of the deep learning models for predicting CK19 status of HCC before surgery.
resultsMultivariate analysis showed that an increased neutrophil-to-lymphocyte ratio (
conclusionThe multi-scale and multi-modality feature fusion model based on MRI and clinical parameters is capable of predicting CK19 status of HCC, demonstrating the feasibility of combining deep learning methods with MRI and clinical features for preoperative prediction of CK19 status.
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