不断发展的人工智能和机器学习技术在精密瘤学中的融合
Elena Fountzilas1, Tillman Pearce2, Mehmet A Baysal3
1Department of Medical Oncology, St Luke's Clinic, Panorama, Thessaloniki, Greece.
NPJ digital medicine
|January 31, 2025
概括
人工智能 (AI) 和机器学习 (ML) 正在通过分析复杂数据来改进癌症诊断和治疗来彻底改变精确瘤学. 在数据集成,算法开发和临床实施方面仍然存在挑战.
科学领域:
- 在瘤学瘤学.
- 生物信息学是一种生物信息学.
- 医疗技术 医疗技术 医学技术
背景情况:
- 精密瘤学旨在为个别患者量身定制癌症治疗.
- 人工智能 (AI) 和机器学习 (ML) 的进步提供了新的分析能力.
- 整合多维数据是理解瘤生物学的关键.
研究的目的:
- 探索AI/ML在推进精密瘤学的作用.
- 突出AI/ML在改善癌症诊断和治疗方面的潜力.
- 确定目前阻碍这些技术广泛采用的挑战.
主要方法:
- 分析多维,多原子,空间病理和放射性数据.
- 应用AI/ML技术用于模式识别和路径识别.
- 合成数据的生成,如数字双胞胎,用于临床试验设计.
主要成果:
- 人工智能/ML能够更深入地了解瘤分子通路.
- 这些技术可以优化癌症患者的治疗选择.
- 合成数据生成可以加快临床试验过程.
结论:
- 对于精确瘤学的未来,AI/ML具有显著的前景.
- 为了成功实施,必须解决运营和技术方面的挑战.
- 需要进一步研究数据共享,概括性和临床工作流集成.
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