Predicting 30-day mortality in severely injured elderly patients with trauma in Korea using machine learning algorithms: a retrospective study
Purpose The number of elderly patients with trauma is increasing; therefore, precise models are necessary to estimate the mortality risk of elderly patients with trauma for informed clinical decision-making. This study aimed to develop machine learning based predictive models that predict 30-day mor...
Saved in:
Main Authors: | Jonghee Han, Su Young Yoon, Junepill Seok, Jin Young Lee, Jin Suk Lee, Jin Bong Ye, Younghoon Sul, Se Heon Kim, Hong Rye Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
Korean Society of Traumatology
2024-09-01
|
Series: | Journal of Trauma and Injury |
Subjects: | |
Online Access: | http://jtraumainj.org/upload/pdf/jti-2024-0024.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Clinical characteristics and mortality risk factors among trauma patients by age groups at a single center in Korea over 7 years: a retrospective study
by: Jonghee Han, et al.
Published: (2023-12-01) -
Geriatric Trauma Outcome Score for Predicting Mortality among Older Korean Adults with Trauma: Is It Applicable in All Cases?
by: Jonghee Han, et al.
Published: (2024-12-01) -
Experience of Penetrating Gunshot Wound on Head in Korea
by: Hong Rye Kim, et al.
Published: (2018-08-01) -
The Influence of Seasons and Weather on the Volume of Trauma Patients: 4 Years of Experience at a Single Regional Trauma Center
by: Se Heon Kim, et al.
Published: (2021-03-01) -
Integrating acute care surgery in South Korea: enhancing trauma and non-trauma emergency care
by: Jin Young Lee, et al.
Published: (2025-01-01)