肝病学中的人工智能:对临床应用,挑战和未来方向的全面范围审查
1Faculty of Medicine and Surgery, Helwan University, Cairo 12511, Egypt.
iLIVER
|December 16, 2025
概括
人工智能 (AI) 在肝病学中显示出重大前景,用于诊断和治疗. 为了负责任的临床整合和改善患者的治疗结果,需要进一步的研究和验证.
科学领域:
- 肝病学 肝病学是一种肝病学.
- 医疗成像医学成像
- 数字病理学数字病理学
- 机器学习 机器学习
- 自然语言处理自然语言处理.
背景情况:
- 人工智能 (AI) 在肝病学中的整合正在增长,但证据是分散的.
- 肝病学中的临床人工智能应用需要系统地绘制和结果总结.
- 人工智能在肝病学中的实施挑战和研究重点需要确定.
研究的目的:
- 系统地绘制肝病学中的临床AI应用.
- 总结人工智能工具在肝病学中的验证结果.
- 确定肝病学AI的实施挑战和研究重点.
主要方法:
- 根据Arksey-O'Malley和Levac框架进行范围审查,根据PRISMA-ScR报告.
- 从2018年1月到2025年7月,对主要数据库 (PubMed,Embase,Scopus,Web of Science,IEEE Xplore) 进行系统搜索.
- 由两名审稿人从3214个记录中进行了独立选和数据提取,包括了75项研究.
主要成果:
- 图像人工智能模型在纤维化阶段,病变检测和体积学方面实现了0.80-0.95的AUC.
- 数字病理学人工智能使得纤维化和肥胖症的客观量化成为可能.
- 机器学习和NLP工具改善了疾病进展,死亡率和并发症检测的预测.
结论:
- 人工智能在肝病学中具有强大的诊断,预后和工作流改善潜力.
- 负责任的人工智能翻译需要多式联运数据,可解释的模型和潜在的验证.
- 以公平为重点的部署策略对于在肝病学中实施人工智能至关重要.
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