Digital twins in oncology.
作者信息
Sager Sebastian
机构信息
Department of Mathematics, Otto von Guericke University, Universitätsplatz 2, Magdeburg, 39106, Germany.
出版信息
J Cancer Res Clin Oncol. 2023 Aug;149(9):5475-5477. doi: 10.1007/s00432-023-04633-1. Epub 2023 Feb 16.
Abstract
摘要
相似文献
1
Digital twins in oncology.肿瘤学中的数字孪生体
J Cancer Res Clin Oncol. 2023 Aug;149(9):5475-5477. doi: 10.1007/s00432-023-04633-1. Epub 2023 Feb 16.
2
Twinning in paediatric oncology - an African experience.儿科肿瘤中的双胞胎现象——一项非洲经验。
S Afr Med J. 2011 Dec 14;102(1):28-9.
3
Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics computational nuclear oncology.用于个性化放射性药物治疗的诊疗数字孪生体：重塑诊疗计算核肿瘤学。
Front Oncol. 2022 Dec 15;12:1062592. doi: 10.3389/fonc.2022.1062592. eCollection 2022.
4
Digital Twins: From Personalised Medicine to Precision Public Health.数字孪生：从个性化医疗到精准公共卫生
J Pers Med. 2021 Jul 29;11(8):745. doi: 10.3390/jpm11080745.
5
On the Integration of Agents and Digital Twins in Healthcare.论医疗保健领域中智能体与数字孪生的整合
J Med Syst. 2020 Aug 4;44(9):161. doi: 10.1007/s10916-020-01623-5.
6
Ethical Issues of Digital Twins for Personalized Health Care Service: Preliminary Mapping Study.数字孪生在个性化医疗保健服务中的伦理问题：初步映射研究。
J Med Internet Res. 2022 Jan 31;24(1):e33081. doi: 10.2196/33081.
7
Mechanistic Mathematical Models as a Basis for Digital Twins.机理数学模型作为数字孪生的基础。
Adv Biochem Eng Biotechnol. 2021;176:133-180. doi: 10.1007/10_2020_152.
8
Metaverse and Healthcare: Machine Learning-Enabled Digital Twins of Cancer.元宇宙与医疗保健：基于机器学习的癌症数字孪生模型
Bioengineering (Basel). 2023 Apr 7;10(4):455. doi: 10.3390/bioengineering10040455.
9
Digital Twins for Bioprocess Control Strategy Development and Realisation.数字孪生在生物工艺控制策略开发和实现中的应用。
Adv Biochem Eng Biotechnol. 2021;177:63-94. doi: 10.1007/10_2020_151.
10
Digital twins for geriatric oncology: Double trouble or twice as nice?老年肿瘤学的数字孪生：双重麻烦还是倍加美好？
J Geriatr Oncol. 2023 Jun;14(5):101524. doi: 10.1016/j.jgo.2023.101524. Epub 2023 May 17.
引用本文的文献
1
Advances and critical aspects in cancer treatment development using digital twins.利用数字孪生技术进行癌症治疗开发的进展与关键方面。
Brief Bioinform. 2025 May 1;26(3). doi: 10.1093/bib/bbaf237.
2
Exploring the Potential of Digital Twins in Cancer Treatment: A Narrative Review of Reviews.探索数字孪生在癌症治疗中的潜力：综述之综述
J Clin Med. 2025 May 20;14(10):3574. doi: 10.3390/jcm14103574.
3
Data-Driven Defragmentation: Achieving Value-Based Sarcoma and Rare Cancer Care Through Integrated Care Pathway Mapping.数据驱动的碎片整理：通过综合护理路径映射实现基于价值的肉瘤和罕见癌症护理
J Pers Med. 2025 May 19;15(5):203. doi: 10.3390/jpm15050203.
4
Mechanisms of isorhamnetin inhibition of osteoclast differentiation: insights from molecular dynamics simulations and / experiments.异鼠李素抑制破骨细胞分化的机制：来自分子动力学模拟和实验的见解
Front Pharmacol. 2025 Apr 28;16:1551257. doi: 10.3389/fphar.2025.1551257. eCollection 2025.
5
Digital Health Technology & Cancer Care: Conceptual Framework Leading Comprehensive Fruitfulness.数字健康技术与癌症护理：引领全面成效的概念框架
J Healthc Leadersh. 2024 Dec 8;16:525-535. doi: 10.2147/JHL.S486263. eCollection 2024.
6
Advancing Precision Oncology with Digital and Virtual Twins: A Scoping Review.利用数字双胞胎和虚拟双胞胎推进精准肿瘤学：一项范围综述。
Cancers (Basel). 2024 Nov 13;16(22):3817. doi: 10.3390/cancers16223817.
7
A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.计算细胞周期模型在指导癌症治疗策略中的综合综述。
NPJ Syst Biol Appl. 2024 Jul 5;10(1):71. doi: 10.1038/s41540-024-00397-7.
8
Theranostic digital twins: Concept, framework and roadmap towards personalized radiopharmaceutical therapies.治疗诊断学数字孪生：个性化放射性药物治疗的概念、框架和路线图。
Theranostics. 2024 May 27;14(9):3404-3422. doi: 10.7150/thno.93973. eCollection 2024.
9
Isorhamnetin: what is the evidence for its antitumor potential and beyond?异鼠李素：其抗肿瘤潜力及其他方面的证据有哪些？
Front Pharmacol. 2024 Apr 8;15:1309178. doi: 10.3389/fphar.2024.1309178. eCollection 2024.
10
A review of mechanistic learning in mathematical oncology.机制学习在数学肿瘤学中的研究综述。
Front Immunol. 2024 Mar 12;15:1363144. doi: 10.3389/fimmu.2024.1363144. eCollection 2024.
本文引用的文献
1
Volatile Organic Compounds From Breath Differ Between Patients With Major Depression and Healthy Controls.重度抑郁症患者与健康对照者呼出的挥发性有机化合物存在差异。
Front Psychiatry. 2022 Jul 12;13:819607. doi: 10.3389/fpsyt.2022.819607. eCollection 2022.
2
Delivering HDAC over 3 or 5 days as consolidation in AML impacts health care resource consumption but not outcome.在 AML 中作为巩固治疗方案，连续 3 天或 5 天给予 HDAC 会影响医疗保健资源的消耗，但不会影响结果。
Blood Adv. 2020 Aug 25;4(16):3840-3849. doi: 10.1182/bloodadvances.2020002511.
3
Model-Based Optimal AML Consolidation Treatment.基于模型的 AML 巩固治疗的最优化。
IEEE Trans Biomed Eng. 2020 Dec;67(12):3296-3306. doi: 10.1109/TBME.2020.2982749. Epub 2020 Nov 19.
4
Optimized and Personalized Phlebotomy Schedules for Patients Suffering From Polycythemia Vera.真性红细胞增多症患者的优化及个性化静脉采血计划
Front Physiol. 2020 Apr 17;11:328. doi: 10.3389/fphys.2020.00328. eCollection 2020.
5
Mathematical Models of Cancer: When to Predict Novel Therapies, and When Not to.癌症的数学模型：何时预测新疗法，以及何时不预测。
Bull Math Biol. 2019 Oct;81(10):3722-3731. doi: 10.1007/s11538-019-00640-x. Epub 2019 Jul 23.
6
Condensed versus standard schedule of high-dose cytarabine consolidation therapy with pegfilgrastim growth factor support in acute myeloid leukemia.高剂量阿糖胞苷巩固治疗联合培非格司亭生长因子支持的浓缩与标准方案在急性髓细胞白血病中的比较。
Blood Cancer J. 2017 May 26;7(5):e564. doi: 10.1038/bcj.2017.45.
7
Improving Cancer Treatment via Mathematical Modeling: Surmounting the Challenges Is Worth the Effort.通过数学建模改善癌症治疗：克服挑战是值得的。
Cell. 2015 Nov 19;163(5):1059-1063. doi: 10.1016/j.cell.2015.11.002.
8
The Norton-Simon hypothesis: designing more effective and less toxic chemotherapeutic regimens.诺顿-西蒙假说：设计更有效且毒性更小的化疗方案。
Nat Clin Pract Oncol. 2006 Aug;3(8):406-7. doi: 10.1038/ncponc0560.
Zotero 插件