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December 8, 2025BloodOpen Access

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

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Authors

SRSharon RuaneMCMingyi ChenAGAnna L. Godfrey

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Overview

Observational analysis enhances risk prediction in vascular events and disease progression in myeloproliferative neoplasms, showing better outcomes than conventional models.

Key Points

  • AI model improves risk prediction for vascular events in myeloproliferative neoplasms, enhancing clinical outcomes.
  • C-index for vascular events improved significantly, outperforming conventional risk models by +5.9%.
  • Utilizing a vision transformer, the model integrates data from bone marrow for dynamic risk assessment.
  • Combining AI with traditional methods enables more reliable identification of high-risk patients for targeted treatments.

Cite This Study

Ruane et al. (2025) studied this question.

synapsesocial.com/papers/69362f694fa91c937236df7dhttps://doi.org/10.1182/blood-2025-5599
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  1. 1A large language model-based framework for automated phenotypic characterization in myeloproliferative neoplasms2025
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  5. 5Molecular predictors of survival in patients with myeloproliferative neoplasm-blast Phase (MPN-BP) treated with venetoclax and decitabine2025 · 1 citations