Artificial intelligence-based application in multiple myeloma
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00259-024-06711-z.pdf
Reference19 articles.
1. Cowan AJ, Green DJ, Kwok M, Lee S, Coffey DG, Holmberg LA, et al. Diagnosis and management of multiple myeloma: a review. JAMA. 2022;327(5):464–77. https://doi.org/10.1001/jama.2022.0003.
2. Caers J, Garderet L, Kortüm KM, O’Dwyer ME, van de Donk NWCJ, Binder M, et al. European myeloma network recommendations on tools for the diagnosis and monitoring of multiple myeloma: what to use and when. Haematologica. 2018;103(11):1772–84. https://doi.org/10.3324/haematol.2018.189159.
3. Greipp PR, San Miguel J, Durie BG, Crowley JJ, Barlogie B, Bladé J, et al. International staging system for multiple myeloma. J Clin Oncol. 2005;23(15):3412–20. https://doi.org/10.1200/JCO.2005.04.242.
4. D’Agostino M, Cairns DA, Lahuerta JJ, Wester R, Bertsch U, Waage A, et al. Second revision of the international staging system (R2-ISS) for overall survival in multiple myeloma: a European myeloma network (EMN) report within the HARMONY project. J Clin Oncol. 2022;40(29):3406–18. https://doi.org/10.1200/JCO.21.02614.
5. Pawlyn C, Davies FE. Toward personalized treatment in multiple myeloma based on molecular characteristics. Blood. 2019;133(7):660–75. https://doi.org/10.1182/blood-2018-09-825331.
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