Hernandez-Boluda, J. C., et al. (2025) Use of machine learning techniques to predict poor survival after hematopoietic cell transplantation for myelofibrosis. Blood. doi.org/10.1182/blood.2024027287.

We propose a deep learning, histopathology image–based risk stratification model that combines clinicopathologic data along with hematoxylin and eosin– and Ki-67–stained histopathology images. We ...

A new machine learning model has significantly improved transplant risk assessment for patients with myelofibrosis, providing a more accurate and data-driven approach to clinical decision-making, ...

Source Reference: Shao Y, et al "Prostate cancer risk stratification by digital histopathology and deep learning" JCO Clin Cancer Inform 2024; DOI: 10.1200/CCI.23.00184.

Session ID: 2025-06-02:53e7819c7398118df180639 Player Element ID: V549421bd_ae15_49c6_a52e_3f6db0222dd3_6331398289112 ...

A machine learning model generated by a team from the European Society for Blood and Marrow Transplantation (EBMT) outperformed standard statistical models in identifying and stratifying ...