Prediction of Suicide-Related Events by Analyzing Electronic Medical Records from PTSD Patients with Bipolar Disorder

Prediction of Suicide-Related Events by Analyzing Electronic Medical Records from PTSD Patients with Bipolar Disorder

Around 800,000 people worldwide die from suicide every year and it’s the 10th leading cause of death in the US. It is of great value to build a mathematic model that can accurately predict suicide especially in high-risk populations. Several different ML-based models were trained and evaluated using...

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Bibliographic Details
Main Authors: Peihao Fan, Xiaojiang Guo, Xiguang Qi, Mallika Matharu, Ravi Patel, Dara Sakolsky, Levent Kirisci, Jonathan C. Silverstein, Lirong Wang
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Brain Sciences
Subjects:
PTSD
bipolar disorder
machine learning
random forest
suicide-related events
model decomposition
Online Access:https://www.mdpi.com/2076-3425/10/11/784

Internet

https://www.mdpi.com/2076-3425/10/11/784

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