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Hassan Raza: A Smarter Risk Prediction in MPNs Using AI
Hassan Raza/LinkedIn
Apr 23, 2026, 07:50

Hassan Raza: A Smarter Risk Prediction in MPNs Using AI

Hassan Raza, Consultant Hematologist and Transfusion Medicine Specialist, shared on LinkedIn about a recent article by Xuezi Hu et al, published in Blood, adding:

”AI Enhancing Risk Prediction in MPNs

A recent American Society of Hematology (Blood 2025) study introduces MEAM – an AI model analyzing bone marrow morphology in ET and PV.

What it does:

Predicts multiple outcomes:
• Thrombosis/bleeding
• Myelofibrosis progression
• AML transformation
• Overall survival

Why it stands out:

Matches or exceeds traditional models (IPSET, R-IPSET-T)

Improves prediction when combined with clinical scores

Detects high-risk patients missed by conventional tools, especially younger patients

Clinical relevance:
Moves morphology from subjective assessment to a quantifiable, dynamic prognostic tool

Takeaway:
AI-integrated morphology may significantly refine risk stratification and treatment decisions in MPNs.”

Title: Multi-endpoint AI morphology model (MEAM) enhances risk prediction for vascular events and disease progression in MPNs

Authors: Xuezi Hu, Alan Aberdeen, Sharon Ruane, Rosalin Cooper, Timothy Ebsworth, Sanam Loghavi, David Ross, Diana Iarossi, Markus Tiemann, Amin Turki, Andrew Sung, Mingyi Chen, Zijun Xu-Monette, Ken Young, Anna Godfrey, Jyoti Nangalia, Joanna Baxter, Anthony Green, Mary Frances McMullin, Adam Mead, Claire Harrison, Jens Rittscher, Korsuk Sirinukunwattana, Daniel Royston

Hassan Raza: A Smarter Risk Prediction in MPNs Using AI

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Adam Mead AI Alan Aberdeen Amin Turki AML Andrew Sung Anna Godfrey Anthony Green ASH bleeding Blood Journals Portfolio Claire Harrison Daniel Royston David Ross Diana Iarossi Hassan Raza Health Hematology Hemostasis Hemostasis News Hemostasis Today Jens Rittscher Joanna Baxter Jyoti Nangalia Ken Young Korsuk Sirinukunwattana Markus Tiemann Mary Frances McMullin MEAM Medicine Mingyi Chen MPNs myelofibrosis Rosalin Cooper Sanam Loghavi Sharon Ruane thrombosis Timothy Ebsworth Xuezi Hu Zijun Xu-Monette
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