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Jun 28, 2024, 12:53

Myeloma Paper of the Day, June 28th, suggested by Robert Orlowski

Robert Orlowski shared a post on X:

“Myeloma Paper of the Day: A deep learning model trained on whole body low dose CT scans may be able to predict the presence of cytogenetic abnormalities used for high risk stratification in myeloma: ”

Source: Robert Orlowski/X

Whole-body low-dose computed tomography in patients with newly diagnosed multiple myeloma predicts cytogenetic risk: a deep learning radiogenomics study

Authors: Shahriar Faghani, Mana Moassefi, Udit Yadav, Francis K. Buadi, Shaji K. Kumar, Bradley J. Erickson, Wilson I. Gonsalves and Francis I. Baffour.

Myeloma Paper of the Day, June 28th, suggested by Robert Orlowski

Other posts featuring Robert Orlowski on OncoDaily.

Robert Orlowski holds multiple positions at The University of Texas MD Anderson Cancer Center, including Chairman, Ad Interim Director of Myeloma, and Professor of Medicine in the Departments of Lymphoma/Myeloma and Experimental Therapeutics within the Division of Cancer Medicine.

Additionally, he chairs the SWOG Barlogie/Salmon Myeloma Committee, which is part of the National Clinical Trials Network, dedicated to advancing new therapies and understanding the biology of myeloma.

Bradley J. Erickson cancer cytogenetic abnormalities Francis I. Baffour Francis K. Buadi high risk stratification low dose CT scans Mana Moassefi MD Anderson Cancer Center Myeloma Myeloma Paper of the Day newly diagnosed multiple myeloma OncoDaily Oncology radiogenomics study Robert Orlowski Shahriar Faghani Shaji K. Kumar Udit Yadav Wilson I. Gonsalves

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