为癌症研究提供的人工智能方法.
Ankita Murmu1,2,3, Balázs Győrffy4,5,6
1Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, Budapest, 1117, Hungary.
Frontiers of medicine
|August 8, 2024
概括
人工智能 (AI) 为癌症研究提供了强大的工具,改善了诊断和治疗选择. 然而,标准化的报告准则对于确保这些AI模型的可重复性和临床应用至关重要.
科学领域:
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
- 医疗保健中的人工智能
背景情况:
- 尽管技术进步,癌症仍然是一个复杂的疾病,在早期诊断和治疗选择方面存在挑战.
- 大规模的多层次数据集提供了潜力,但需要先进的生物信息工具用于临床应用.
- 人工智能 (AI) 正在成为将癌症数据转化为可操作的见解的关键技术.
研究的目的:
- 审查AI方法在癌症研究中的多样化应用.
- 探索AI在临床决策支持中的好处和局限性.
- 总结医疗保健中人工智能的指导方针,并讨论未来对癌症研究的影响.
主要方法:
- 审查机器学习技术,包括贝叶斯网络,支持向量机器,决策树,随机森林,梯度增强,K-最近邻居和深度学习.
- 探索大型语言模型,用于在瘤学中解决新问题.
- 对医疗保健中人工智能的现有报告准则进行分析,以应对可重复性挑战.
主要成果:
- 包括深度学习在内的AI方法在癌症预测,预后和诊断研究中具有显著价值.
- 大型语言模型正在探索癌症研究的新应用.
- 缺乏标准化的报告准则阻碍了AI研究在临床环境中的可重复性.
结论:
- 人工智能具有很大的潜力,可以促进癌症的诊断,治疗和研究.
- 遵守报告准则对于提高人工智能模型的可靠性和临床翻译至关重要.
- 未来的癌症研究很可能会受到人工智能的持续发展和应用的重大影响.
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