Arman Oganisian: Our work developing Bayesian machine learning methods for sequential treatment strategies in AML

Arman Oganisian, Assistant Professor of Biostatistics at Brown University, shared the following on LinkedIn:

“Happy to share that our work developing Bayesian machine learning methods for sequential treatment strategies in acute myeloid leukemia (AML) was just published in Biostatistics.

Treatment for AML, like many diseases, is not “one-and-done” but instead involves tailoring therapies over time as the patient’s condition evolves. How (and when) to modify therapies to maximize survival is one of the key questions in this area.

Working with collaborators at the Children’s Hospital of Philadelphia, these methods were used to estimate treatment strategies that maximize survival under certain conditions.

This work is partially funded by Patient-Centered Outcomes Research Institute (PCORI).”

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Source: Arman Oganisian/LinkedIn