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-Powered OCT Enables Rapid 'Optical Biopsy' for Early Endometrial Cancer Detection
A team at Washington University has developed a catheter-based 3D OCT system with AI to quickly and noninvasively detect early endometrial cancers.
•EurekAlert
AI Clinical Reasoning in Diagnostics and Digital Fatigue in Healthcare
Recent JMIR features explore large language models in clinical diagnostics and digital fatigue among healthcare professionals.
•EurekAlert
KAIST, MIT, Microsoft Develop Efficient AI Image Upsampling for Robotics
KAIST, MIT, and Microsoft have created 'Upsample Anything,' a training-free AI method to restore high-resolution visual data from compressed images with up to 16x improved GPU memory efficiency.