Machine learning characterization of cancer patients-derived extracellular vesicles using vibrational spectroscopies: results from a pilot study.
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-03203-1.pdf
Reference55 articles.
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2. Théry C et al (2018) Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines. J Extracell Vesicles 7:1535750
3. Uthamacumaran A (2020) A review of complex systems approaches to Cancer networks. Complex Systems 29(4):779–835
4. Samuel P, Fabbri M, Carter DRF (2017) Mechanisms of drug resistance in Cancer: the role of extracellular vesicles. Proteomics 17(23-24):1600375. https://doi.org/10.1002/pmic.201600375
5. Ramakrishnan V, Xu B, Akers J, Nguyen T, Ma J, Dhawan S et al (2020) Radiation-induced extracellular vesicle (EV) release of miR-603 promotes IGF1-mediated stem cell state in glioblastomas. EBioMedicine 55:102736. https://doi.org/10.1016/j.ebiom.2020.102736
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