A review: Prediction model for the incidence rate of intracerebral hemorrhage

DOI

10.2991/itoec-16.2016.80How to use a DOI?

Keywords

Intracerebral hemorrhage; artificial intelligence; Computed tomography angiography (CTA)

Abstract

Intracerebral hemorrhage (ICH) accounts for around 10-30% incidence of the cerebral apoplexy, the prognosis of which is so poor that has high morbidity and mortality. In cerebral hemorrhage, the artery bleeding is very common. Along with the development of imaging, computed tomography angiography (CTA) can be used to predict the incidence of intracerebral hemorrhage. Based on the previous studies for ICH. This study proposed such a novel mathematical model for the incidence of cerebral hemorrhage prediction that not only investigated the potential risk factors ICH, but also employed CTA images and statistic test to explore which potential risk factors can be used as the classifier of the mathematical model. Next, we used training data set to train the weight of these selected risk factors by artificial intelligence algorithm as well as employed testing data to validate the predictive power of the model. We expected this mathematical model can be be able to predict the incidence rate of cerebral hemorrhage and offer the corresponding preventive suggestion in the distant future.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Kaikai Yin
AU  - Le Zhang
AU  - Hua Feng
AU  - Rong Hu
PY  - 2016/05
DA  - 2016/05
TI  - A review: Prediction model for the incidence rate of intracerebral hemorrhage
BT  - Proceedings of the 2nd Information Technology and Mechatronics Engineering Conference (ITOEC 2016)
PB  - Atlantis Press
SP  - 417
EP  - 421
SN  - 2352-5401
UR  - https://doi.org/10.2991/itoec-16.2016.80
DO  - 10.2991/itoec-16.2016.80
ID  - Yin2016/05
ER  -