Mr. Chia-Wen Hsu Profile

Chia-Wen Hsu

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 5 February 2025 Paper

Predicting 14-day unplanned hospital readmissions using machine learning and explainable artificial intelligence

Wen-Lin Fan, Chun-Chi Chuang, Chieh-Chi Huang, Chia-Wen Hsu, TASI-TING HSU, Ting-Rui Guo, Chung-Chian Hsu

Proceedings Volume 13510, 1351018 (2025) https://doi.org/10.1117/12.3057997

Read Abstract +

Unplanned readmission within 14 days is a critical indicator of healthcare quality, impacting patient risk, costs, and hospital reputations. This study explores the use of machine learning to predict unplanned hospital readmissions within 14 days and explainable artificial intelligence techniques to identify key risk factors. Patient data, such as age, gender, and hospital stay length, were used to create a prediction model based on artificial neural networks. Techniques like class weighting were applied to improve the prediction of less common cases. Shapley Additive Explanations and Integrated Gradients methods were used to explain the model, making it easier to understand and use in clinical settings. The results show that the model improves the accuracy of readmission risk predictions, helps healthcare professionals find high-risk patients early, and supports timely interventions to improve care quality and reduce readmissions.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years