Using machine learning for outcome prediction of patients with severe head injury

The paper presents an application of decision tree induction to the problem of the prediction of outcome after a severe head injury. The study shows that induced decision trees are useful for the analysis of the importance of clinical parameters and of their combinations for the evaluation of the se...

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Main Authors: Pilih, I.A., Mladenic, D., Lavrac, N., Prevec, T.S.
Format: Conference Proceeding
Language:English
Subjects:
Brain injuries
Decision trees
Hospitals
Machine learning
Magnetic heads
Mathematical model
Protocols
Statistical analysis
Surgery
Tomography
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creator Pilih, I.A.
Mladenic, D.
Lavrac, N.
Prevec, T.S.
description The paper presents an application of decision tree induction to the problem of the prediction of outcome after a severe head injury. The study shows that induced decision trees are useful for the analysis of the importance of clinical parameters and of their combinations for the evaluation of the severity of brain injury and for outcome prediction.
doi_str_mv 10.1109/CBMS.1997.596434
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Brain injuries
Decision trees
Hospitals
Machine learning
Magnetic heads
Mathematical model
Protocols
Statistical analysis
Surgery
Tomography
title Using machine learning for outcome prediction of patients with severe head injury
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