Researchers use machine learning to predict adverse events during stem cell therapy for multiple myeloma, improving outpatient safety.
Key Details
- 1Researchers analyzed data from 109 multiple myeloma patients undergoing stem cell mobilization.
- 2Machine learning models identified time periods with low risk for serious side effects during therapy.
- 3Models could accurately predict the timing and occurrence of certain side effects in individual patients.
- 4Enables more patients to safely undergo chemotherapy and stem cell mobilization as outpatients.
- 5Outpatient treatment improves quality of life and allows for better hospital resource management.
- 6Findings published in npj Digital Medicine by Göttingen and Bielefeld researchers.
Why It Matters
By accurately stratifying patient risk using AI, more multiple myeloma patients could receive therapy outside the hospital, reducing healthcare costs and improving patient experience. This study highlights the growing role for AI in personalizing oncology care pathways.
Source
EurekAlert
Related News
•EurekAlert
AI Accelerates Radiopharmaceuticals, Boosts Personalized Dosimetry in Cancer
Machine learning is driving advancements in radiopharmaceutical drug discovery and optimizing patient-specific dosimetry for precision cancer therapy.
•EurekAlert
Physicians Overly Trust Erroneous AI, Ignore Contradictory Evidence
Physicians tend to trust incorrect AI advice, even when evidence contradicts it, suggesting risks in clinical decision-making with AI tools.
•EurekAlert
Concerns Raised Over Unverified Datasets in AI Health Prediction Models
A new study finds widely used AI health prediction models are built on datasets with unverifiable origins, raising safety and validity concerns.