The Know AML 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 Know AML cannot guarantee the accuracy of translated content. Know AML 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 can big data help to better classify acute myeloid leukemia subtypes?
Lars Bullinger
June 17, 2020
During the 25th Congress of the European Hematology Association (EHA), KnowAML spoke to Lars Bullinger, Charité – Universitätsmedizin Berlin, Berlin, DE. The term 'acute myeloid leukemia' covers many different disease states, and individual cases are characterized by genetic aberrations, which cause the transition from normal cells to cancer cells. Efforts have been made to better understand these differences. As a result, treatments are now more personalized to individual patients, and improved patient outcomes have been observed.
To what extent do you agree with the following statements?
Please rate between 1 and 5, with 1 being 'strongly disagree' and 5 being 'strongly agree'.
