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机器学习在肝脏疾病中的应用现状和未来趋势

李 富源, 汪 占金, 蔡 俊杰, 薛 张佗, 周 瀛

摘要

随着计算能力的提升和数据量的增加,机器学习(ML)在医疗领域的应用越来越广泛,尤其是在肝脏疾病的早期诊断、
风险评估和治疗决策中。本文综述了机器学习在肝脏疾病中的关键应用,包括寻找肝癌的潜在标志物、预测肝脏术后并发症、
识别肝脏疾病的早期危险因素,以及结合影像组学等方面的应用现状与未来趋势。通过分析现有研究,探讨机器学习在肝
脏疾病管理中的潜力与挑战。

关键词

机器学习;肝脏疾病;风险评估;肝包虫病

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