E-046 Length of stay in mechanical thrombectomy, and machine learning improvement of predictive analysis

Conclusions Machine learning methods outperform multivariate logistic regression at the prediction of length of stay. Predictive analysis for patient length of stay could help hospital utilization and allow for more aggressive measures to prevent hospital acquired conditions. Disclosures S. Arndt: None. G. Bennett: None. K. Wojcik: None. A. Albar: None. M. Alhasan: None. J. Ma: None. P. Gulotta: None. J. Milburn: None.

http://jnis.bmj.com/cgi/content/short/9/Suppl_1/A64-a?rss=1

Source: Journal of NeuroInterventional Surgery - July 23, 2017 Category: Neurosurgery Authors: Arndt, S., Bennett, G., Wojcik, K., Albar, A., Alhasan, M., Ma, J., Gulotta, P., Milburn, J. Tags: Electronic Poster Abstracts Source Type: research