ASH 2023 | Use of machine learning to predict outcomes for patients with SCD
Nirmish Shah, MD, Duke University, Durham, NC, explores the application of technology to predict outcomes for patients with sickle cell disease (SCD). The study involved utilizing physiologic data monitored by Apple watches to predict the 30-day re-admission rate of patients. By integrating this information with medical records, comorbidity data, and lab data, machine learning can be employed to predict outcomes for these patients. This interview took place at the 65th ASH Annual Meeting and Exposition, held in San Diego, CA.
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Disclosures
Advisory board: Agios, Bluebird Bio, CSL Behring, Emmaus, Forma Therapeutics, Novo Nordisk, Pfizer, Vertex
Research Funding: Pfizer
Speakers Bureau: Pfizer, Alexion, Novartis
