辐射瘤学中的AI:对当前应用和未来方向的全面审查
Fabeha Zafar1, Jessica Vilsan2, Shinjit Mani3
1Department of Internal Medicine, Dow University of Health Sciences, Karachi, PAK.
Cureus
|October 24, 2025
概括
人工智能 (AI) 通过提高治疗计划,治疗和预测结果的效率和准确性来增强放射性瘤学. 虽然人工智能提供了显著的进步,但必须解决数据质量,验证和伦理考虑方面的挑战,以实现全面的临床整合.
科学领域:
- 辐射瘤学 辐射瘤学
- 医学物理 医学物理
- 计算机科学 计算机科学
- 医学中的人工智能
背景情况:
- 放射性瘤学结合了物理,数学,计算机科学,生物学和医学.
- 人工智能 (AI) 在医学领域的应用越来越多,包括放射治疗.
研究的目的:
- 总结当前在辐射瘤学中的AI应用.
- 在放射治疗工作流程中映射AI集成.
- 分析AI在放射治疗中的贡献,进步,局限性和未来方向.
主要方法:
- 审查目前在放射瘤学中人工智能使用情况.
- 分析机器学习软件对效率和准确性的影响.
- 检查AI在图像重建,细分,交付和结果预测中的作用.
主要成果:
- 人工智能提高了辐射治疗规划,交付和结果预测的效率和准确性.
- 深度学习增强了细分,减少了规划和交付时间.
- 人工智能的预测能力有助于预测和减少治疗毒性.
结论:
- 人工智能集成保证了质量,标准化,并减少了放射治疗工作流程的变化.
- 高质量,符合隐私的数据对于强大的AI模型至关重要.
- 伦理和后勤方面的挑战,包括临床验证和可重复性,需要关注人工智能与人类监督的无整合.
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