Learning, Optimization & Design for Healthcare Systems
نویسندگان
چکیده
We are interested in fundamental decision and design problems in human-machine collaboration and skill-augmentation, with a focus on healthcare. Inference and optimization in healthcare are often hard multi-stage stochastic models, but we explore efficient reformulations and heuristics with guarantees. Specifically, we have studied algorithmically grounded solutions for integration of autonomy in internal radiotherapy for cancer and subtask automation in Robot-assisted minimally invasive surgery (RMIS).
منابع مشابه
Policy Capacity in the Learning Healthcare System; Comment on “Health Reform Requires Policy Capacity”
Pierre-Gerlier Forest and his colleagues make a strong argument for the need to expand policy capacity among healthcare actors. In this commentary, I develop an additional argument in support of Forest et al view. Forest et al rightly point to the need to have embedded policy experts to successfully translate healthcare reform policy into healthcare change. Translation of externally generated i...
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