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24 April 2024 |
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Article overview
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Hepatocellular Carcinoma Intra-arterial Treatment Response Prediction for Improved Therapeutic Decision-Making | | Junlin Yang
; Nicha C. Dvornek
; Fan Zhang
; Julius Chapiro
; MingDe Lin
; Aaron Abajian
; James S. Duncan
; | | Date: |
1 Dec 2019 | | Abstract: | This work proposes a pipeline to predict treatment response to intra-arterial
therapy of patients with Hepatocellular Carcinoma (HCC) for improved
therapeutic decision-making. Our graph neural network model seamlessly combines
heterogeneous inputs of baseline MR scans, pre-treatment clinical information,
and planned treatment characteristics and has been validated on patients with
HCC treated by transarterial chemoembolization (TACE). It achieves Accuracy of
$0.713 pm 0.075$, F1 of $0.702 pm 0.082$ and AUC of $0.710 pm 0.108$. In
addition, the pipeline incorporates uncertainty estimation to select hard cases
and most align with the misclassified cases. The proposed pipeline arrives at
more informed intra-arterial therapeutic decisions for patients with HCC via
improving model accuracy and incorporating uncertainty estimation. | | Source: | arXiv, 1912.0411 | | Services: | Forum | Review | PDF | Favorites | |
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