Work

Which molecular patterns of high-risk myeloid malignancies are concordantly identified using two machine learning algorithms?

Year: 2025

Type: conference-abstract

Source: Blood

DOI: 10.1182/blood-2025-3485

Authors: Tariq Kewan, Arda Durmaz, Waled Bahaj, Carmelo Gurnari, Olisaemeka Ogbue, Matteo D'Addona, Ahmad Kiwan, Hussein Awada, Simona Pagliuca, Hetty Carraway, Amer Zeidan, Suresh Kumar Balasubramanian, Taha Bat, Yazan Madanat, Valeria Visconte, Jaroslaw Maciejewski

Institutions: Mayo Clinic, Cleveland Clinic, University of Rome Tor Vergata, Yale New Haven Hospital, Yale University, Yale Cancer Center, Wayne State University, The Barbara Ann Karmanos Cancer Institute, The University of Texas Southwestern Medical Center

Language: English

Topic: Acute Myeloid Leukemia Research

Subfield: Hematology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4417009059

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