Charles Sturt University, NSW, Australia; Baylor College of Medicine, TX.
Charles Sturt University, NSW, Australia; Baylor College of Medicine, TX.
Semin Nucl Med. 2023 May;53(3):457-466. doi: 10.1053/j.semnuclmed.2022.10.007. Epub 2022 Nov 12.
Developments in artificial intelligence, particularly convolutional neural networks and deep learning, have the potential for problem solving that has previously confounded human intelligence. Accurate prediction of radiation dosimetry pre-treatment with scope to adjust dosing for optimal target and non-target tissue doses is consistent with striving for improved the outcomes of precision medicine. The combination of artificial intelligence and production of digital twins could provide an avenue for an individualised therapy doses and enhanced outcomes in theranostics. While there are barriers to overcome, the maturity of individual technologies (i.e. radiation dosimetry, artificial intelligence, theranostics and digital twins) places these approaches within reach.
人工智能的发展，特别是卷积神经网络和深度学习，具有解决以前困扰人类智能的问题的潜力。准确预测放射治疗剂量，并有机会调整剂量以实现最佳靶区和非靶区组织剂量，这与努力提高精准医学的结果是一致的。人工智能与数字孪生的结合，为个体化治疗剂量和改善治疗效果提供了途径。虽然还有许多障碍需要克服，但个别技术的成熟度（即放射治疗剂量学、人工智能、治疗学和数字孪生）使这些方法变得可行。
