A new machine learning prediction model for thrombosis risk in polycythemia vera

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Ghaith Abu-Zeinah, MD, Weill Cornell Medicine and the New York Presbyterian Hospital, New York City, NY, discusses a novel machine learning prediction model for thrombosis risk in polycythemia vera (PV), highlighting the limitations of current risk stratification models. Dr Abu-Zeinah explains that this model utilizes a vast amount of real-world data and comments on how they expect to validate the model in the future to be used more widely in a clinical setting for PV. This interview took place at the 14th International Congress on Myeloproliferative Neoplasms (MPN Congress) held in New York City, NY.

These works are owned by Magdalen Medical Publishing (MMP) and are protected by copyright laws and treaties around the world. All rights are reserved.
  1. VJHemOnc – Video Journal of Hematology & HemOnc
  2. Speaker: Ghaith Abu-Zeinah
  3. Institution: Weill Cornell Medicine and the New York Presbyterian Hospital
  4. Event: MPN Congress 2022
  5. Format: Interview
  6. Subject: Myeloproliferative Neoplasms
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