This article is about the development of a nurse turnover prediction model in Korea using machine learning. The model has been created by MDPI, a publication platform dedicated to scientific research. MDPI allows any part of the articles published to be reused without permission under an open access Creative Commons CC BY license, as long as the original article is properly cited. With this model, healthcare administrators will be able to more accurately predict nurse turnover and adjust their nurse staffing strategies in response.
MDPI is a leading open access provider of scholarly publications, providing peer-reviewed research across multiple industries. Since 2010, MDPI has dedicated itself to making scientific research freely accessible to everyone. All articles published are under an open access license, allowing anyone to access and reuse the content of any article without obtaining further permission. This has helped make scientific information freely available to all, wherever it is required.
The person in this article is Prof. Hang-Bae Cho. Prof. Cho is the Head of the Department of Biomedical Informatics and Computer Science at the Seoul National University Biomedical Research Institute in Korea. He has worked on a number of machine learning-related projects, particularly in the area of healthcare. One of his most recent projects is the development of this nurse turnover prediction model. The model uses machine learning techniques such as deep neural networks to generate accurate predictions of nurse turnover.
By using this prediction model, healthcare administrators will be able to more accurately predict nurse turnover. This will help them make better staffing decisions in order to adequately prepare for any possible changes in nurse staff. By doing so, they can provide better healthcare services to their patients.
To sum up, this article discussed the development of a nurse turnover prediction model in Korea using machine learning. The model has been developed by Prof. Hang-Bae Cho and his team from the Seoul National University Biomedical Research Institute. It uses machine learning techniques such as deep neural networks to generate accurate predictions of nurse turnover. This prediction model will help healthcare administrators prepare for any changes in nurse staff and provide better services to their patients.
