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Application of machine learning in predicting survival outcomes involving real-world data: a scoping review
67
Zitationen
4
Autoren
2023
Jahr
Abstract
The ML algorithms, random survival forests and neural networks, are mainly used for RWD to predict survival outcomes such as disease prognosis or clinical events in the oncology. This review shows that more opportunities remain to apply these ML algorithms to inform treatment decision-making in clinical practice. More methodological work is also needed to ensure the utility and applicability of ML models in survival outcomes.
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