- Correspondence to letter to the editor 1 on “Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma”
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Ho CT, Tan ECH, Su CW
- KMID: 2563471
- Clin Mol Hepatol.
- 2025 Jan;31(1):e96-e97.
- doi: 10.3350/cmh.2024.0999
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- Correspondence to letter to the editor 2 on “Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma”
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Ho CT, Tan ECH, Su CW
- KMID: 2563473
- Clin Mol Hepatol.
- 2025 Jan;31(1):e101-e102.
- doi: 10.3350/cmh.2024.0946
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- Correspondence to editorial on “Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma”
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Ho CT, Tan ECH, Su CW
- KMID: 2560113
- Clin Mol Hepatol.
- 2024 Oct;30(4):1016-1018.
- doi: 10.3350/cmh.2024.0365
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- Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma
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Ho CT, Tan ECH, Lee PC, Chu CJ, Huang YH, Huo TI, Su YH, Hou MC, Wu JC, Su CW
- KMID: 2557392
- Clin Mol Hepatol.
- 2024 Jul;30(3):406-420.
- doi: 10.3350/cmh.2024.0103
Background/Aims: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML... -
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