Identifying Important Attributes for Prognostic Prediction in Traumatic Brain Injury Patients. A Hybrid Method of Decision Tree and Neural Network.

Journal: Methods of information in medicine

PMID: 27492342

Abstract

BACKGROUND: Generally, traumatic brain injury (TBI) patients do not have a stable condition, particularly after the first week of TBI. Hence, indicating the attributes in prognosis through a prediction model is of utmost importance since it helps caregivers with treatment-decision options, or prepares the relatives for the most-likely outcome.

Authors

Saeedeh Pourahmad

1: Colorectal research center, Shiraz University of Medical Sciences, Shiraz, Iran 2: Department of Biostatistics, Shiraz University of Medical Sciences, Shiraz, Iran. pourahmad@sums.ac.ir.
Iman Hafizi-Rastani
Hosseinali Khalili
Shahram Paydar

Keywords

Adult Aged Brain Injuries, Traumatic Decision Trees Glasgow Outcome Scale Humans Middle Aged Models, Theoretical Neural Networks, Computer Prognosis

External Resources

View on PubMed Access via DOI PubMed (27492342)

Identifying Important Attributes for Prognostic Prediction in Traumatic Brain Injury Patients. A Hybrid Method of Decision Tree and Neural Network.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals