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Automated and interoperable methods for generalizable development of clinical machine-learning models for predicting neuromorbidity in critically ill children
1
Zitationen
9
Autoren
2025
Jahr
Abstract
This study demonstrates the feasibility of a cloud-compatible, standards-based approach to clinical ML model development. By leveraging interoperable data formats and automated modeling workflows, this approach supports scalable, reproducible model construction and evaluation, enabling improved efficiency and transparency in clinical decision support.
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