All content on this site is intended for healthcare professionals only. By acknowledging this message and accessing the information on this website you are confirming that you are a Healthcare Professional. If you are a patient or carer, please visit the International Myeloma Foundation or HealthTree for Multiple Myeloma.
The Multiple Myeloma Hub uses cookies on this website. They help us give you the best online experience. By continuing to use our website without changing your cookie settings, you agree to our use of cookies in accordance with our updated Cookie Policy
An expert panel hosted by
Sequencing immune-based therapies in B-cell malignancies
with Ulric Jäger, Sagar Lonial, and Krina Patel
Saturday, June 15 | 18:00-19:30 CEST
Register nowThis independent education activity is sponsored by Bristol Myers Squibb. All content is developed independently by the faculty. Funders are allowed no direct influence on the content of this activity.
The Multiple Myeloma Hub website uses a third-party service provided by Google that dynamically translates web content. Translations are machine generated, so may not be an exact or complete translation, and the Multiple Myeloma Hub cannot guarantee the accuracy of translated content. The Multiple Myeloma Hub and its employees will not be liable for any direct, indirect, or consequential damages (even if foreseeable) resulting from use of the Google Translate feature. For further support with Google Translate, visit Google Translate Help.
How might AI be incorporated into the diagnosis and management of MM?
Featured
During the 5th European Myeloma Network Meeting, the Multiple Myeloma Hub was pleased to speak with Adrián Mosquera Orgueira, University of Santiago de Compostela, Santiago, ES. We asked, How might artificial intelligence (AI) be incorporated into the diagnosis and management of multiple myeloma?
How might AI be incorporated into the diagnosis and management of MM?
Adrián Mosquera Orgueira opens by emphasizing the importance of standardization of both diagnostic and prognostic tools in multiple myeloma (MM). He goes on to discuss how AI could be utilized to achieve this, particularly in more complex indicators such as measurable residual disease (MRD) and risk status. Mosquera Orgueira further highlights the predictive capability of AI to use patient profiles to determine which individuals will receive the most benefit from therapy, therefore helping tailor individualized treatment approaches.
Related articles
Newsletter
Subscribe to get the best content related to multiple myeloma delivered to your inbox