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ASH 2022 | A machine learning model to improve outcome prediction following allogeneic transplantation

Akshay Sharma • 12 Dec 2022
ASH 2022
General

Akshay Sharma, MBBS, St. Jude Children’s Research Hospital, Memphis, TN, discusses the key features and advantages of a new model using machine learning to combine baseline and high-dimensional longitudinal data to improve the prediction of overall survival (OS) following allogeneic transplantation in patients with hematological malignancies. This interview took place at the 64th ASH Annual Meeting and Exposition congress in New Orleans, LA.

These works are owned by Magdalen Medical Publishing (MMP) and are protected by copyright laws and treaties around the world. All rights are reserved.

Disclosures

Spotlight Therapeutics: Consultancy; CRISPR Therapeutics: Other: Clinical Trial Site PI, Research Funding; Novartis: Other: Clinical Trial Site PI; Magenta Therapeutics: Other: Clinical Trial Site PI; Vindico Medical Education: Honoraria; Medexus Inc: Consultancy; Vertex Pharmaceuticals/CRISPR Therapeutics: Consultancy, Membership on an entity’s Board of Directors or advisory committees, Other: Clinical Trial Site PI.

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