NeuroIS knowledge discovery approach to prediction of traumatic brain injury survival rates: A semantic data analysis regression feasibility study

Lecture Notes in Information Systems and Organisation

Volumn 10, Issue , 2015, Pages 1-8

  Rodger, James A ^a  

^a INDIANA UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Apache Hive Informatics; Decision support; Neuro IS; Traumatic brain injuries

Indexed keywords

EID: 84946197792     PISSN: 21954968     EISSN: 21954976     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-319-18702-0_1     Document Type: Chapter

References (12)

1. Hazen, B.T., Boone, C.A., Ezell, J.D., Jones-Farmer, L.A.: Data quality for data science, predictive analytics, and big data in supply chain management: an introduction to the problem and suggestions for research and applications. Int. J. Prod. Econ. 154, 72-80 (2014)
2. Edwards, M., Rambani, A., Zhu, Y., Musavi, M.: Design of hadoop-based framework for analytics of large synchrophasor datasets. Procedia Comput. Sci. 12, 254-258 (2012)
3. Shina, S.-J., Wooa, J., Rachuria, S.: Predictive analytics model for power consumption in manufacturing. Procedia CIRP 15, 153-158 (2014)
4. Seera, M., Lim, C.P.: A hybrid intelligent system for medical data classification. Expert Syst. Appl. 41, 2239-2249 (2014)
5. Esfandiari, N., Babavalian, M.R., Moghadam, A.-M.E., Tabar, V.K.: Knowledge discovery in medicine: current issue and future trend. Expert Syst. Appl. 41, 4434-4463 (2014)
6. García-Rudolph, A., Gibert, K.: A data mining approach to identify cognitive neurorehabilitation range in traumatic brain injury patients. Expert Syst. Appl. 41, 5238-5251 (2014)
7. Marcano-Cedeño, A., Chausa, P., García, A., Cáceres, C., Tormos, J.M., Gómez, E.J.: Data mining applied to the cognitive rehabilitation of patients with acquired brain injury. Expert Syst. Appl. 40, 1054-1060 (2013)
8. Hatiboglu, M.A., Altunkaynak, A., Ozger, M., Iplikcioglu, A.C., Cosar, M., Turgut, N.: A predictive tool by fuzzy logic for outcome of patients with intracranial aneurysm. Expert Syst. Appl. 37, 1043-1049 (2010)
9. Güler, I., Gökçil, Z., Gülbandilar, E.: Evaluating of traumatic brain injuries using artificial neural networks. Expert Syst. Appl. 36, 10424-10427 (2009)
10. Lu, J., Marmarou, A., Lapane, K.L.: Impact of GOS misclassification on ordinal outcome analysis of traumatic brain injury clinical trials. J. Neurotrauma 29(5), 719-726 (2011)
11. Kao, C.-H., Nakano, J., Shieh, S.-H., Tien, Y.-J., Wu, H.-M., Yang, C.-K., Chen, C.-H.: Exploratory data analysis of interval-valued symbolic data with matrix visualization. Comput. Stat. Data Anal. 79, 14-29 (2014)
12. Guo, J., Li, W., Li, C., Gao, S.: Standardization of interval symbolic data based on the empirical descriptive statistics. Comput. Stat. Data Anal. 56, 602-610 (2012)