An investigation of data mining techniques of the performance of a decision tree algorithm for predicting causes of traumatic brain injuries in Khatamolanbya Hospital in Zahdan city, 2012 to 2013
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Summary
It can be concluded from the decision tree algorithm that age is one of the leading causes of traumatic brain injuries, and all the cases involving traumatic lesions of the brain lead to the patient’s death.
- Type
- article
- Published
- 2014-04-10
- Cited by
- 0
- References
- 13
- Access
- Open access
- OpenAlex
- https://openalex.org/W1910644451
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:58818831
Keywords
Decision tree, Computer science, Traumatic brain injury, Data mining, Decision tree learning
References
- Incidence of Hospital-Treated Traumatic Brain Injury in the Oslo Population
- Managing Health Care Information Systems: A Practical Approach for Health Care Executives
- Clinical knowledge management : opportunities and challenges
- Creating knowledge-based healthcare organizations
- Innovative data mining approaches for outcome prediction of trauma patients
- Death and disability from injury: a global challenge.
- Epidemiology of traumatic brain injury in eastern China, 2004: a prospective large case study.
- Keeping up: learning in the workplace
- Data warehouse implementation& Data mining: Efficient Data Cubecomputation: An overview, Indexing OLAP Data: Bitmap index and join index,Efficient processing of OLAP Queries, OLAP server Architecture ROLAP versusMOLAP Versus HOLAP : Introduction: What is data mining, Challenges, DataMining Tasks
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