Mr. Hai Jia Profile

Hai Jia

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 | 6 December 2022 Paper

Small sample medical event extraction based on data augmentation

Manfu Ma, Xiaoxue Li, Yong Li, Xinyu Zhao, Xia Wang, Hai Jia

Proceedings Volume 12458, 124583N (2022) https://doi.org/10.1117/12.2660281

KEYWORDS: Data modeling, Tumors, Systems modeling, Performance modeling, Machine learning

Read Abstract +

The key problem of event extraction in the medical field is that the cost of medical data labeling is too high, and the labeled samples are scarce, making medical event extraction difficult. In response to this problem, this paper proposes to perform a partial synonymous replacement of training samples to expand the data, and the data and the original data together constitute new electronic medical record data (i.e. EDA data enhancement); In addition, the unlabeled data is predicted by the medical event extraction model to generate labeled data, and then the accurate labeled data is filtered out and added to the original data to form new electronic medical record data, thereby realizing data enhancement (i.e. UDF data enhancement) , to a certain extent, to solve the problem of the scarcity of medical data samples. Based on augmented data, a medical event extraction model (i.e. TEC_MEE model) based on Transformer Encoder and CRF are constructed to extract attributes of specified events from unstructured Chinese electronic medical record text. The experimental results show that, compared with the baseline model, the TEC_MEE model proposed in this paper obtains better medical event extraction results after data enhancement.

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