Development of Synthetic Patient Populations and In Silico Clinical Trials-Reference-Cited by-同舟云学术

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Development of Synthetic Patient Populations and In Silico Clinical Trials

Published:2018 Issue: Volume: Page:57-77
ISSN:
Container-title:Accelerated Path to Cures
language:
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Author:

Zand Ramin,Abedi Vida,Hontecillas Raquel,Lu Pinyi,Noorbakhsh-Sabet Nariman,Verma Meghna,Leber Andrew,Tubau-Juni Nuria,Bassaganya-Riera Josep

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-73238-1_5

Reference57 articles.

1. Abedi V et al (2016) Phase III placebo-controlled, randomized clinical trial with synthetic crohn’s disease patients to evaluate treatment response. In: Emerging trends in applications and infrastructures for computational biology, bioinformatics, and systems biology. Elsevier, Cambridge, MA, pp 411–427. https://doi.org/10.1016/B978-0-12-804203-8.00028-6

2. Abedi V et al (2017) Novel screening tool for stroke using artificial neural network. Stroke 48:1678–1681. https://doi.org/10.1161/STROKEAHA.117.017033

3. Abul-Husn NS et al (2016) Genetic identification of familial hypercholesterolemia within a single U.S. health care system. Science 354:pii: aaf7000. https://doi.org/10.1126/science.aaf7000

4. Aerts JM, Haddad WM, An G, Vodovotz Y (2014) From data patterns to mechanistic models in acute critical illness. J Crit Care 29:604–610. https://doi.org/10.1016/j.jcrc.2014.03.018

5. Allen RJ, Rieger TR, Musante CJ (2016) Efficient generation and selection of virtual populations in quantitative systems pharmacology models. CPT Pharmacometrics Syst Pharmacol 5:140–146. https://doi.org/10.1002/psp4.12063

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups;BMC Medical Research Methodology;2024-09-09

2. Assessing the Role of Patient Generation Techniques in Virtual Clinical Trial Outcomes;Bulletin of Mathematical Biology;2024-08-13

3. High-Fidelity Synthetic Data Applications for Data Augmentation;Artificial Intelligence;2024-05-29

4. Generating synthetic multidimensional molecular time series data for machine learning: considerations;Frontiers in Systems Biology;2023-07-25

5. Synthetic data in health care: A narrative review;PLOS Digital Health;2023-01-06

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