Skip to Main Content

An official website of the United States government

Government Funding Lapse

Because of a lapse in government funding, the information on this website may not be up to date, transactions submitted via the website may not be processed, and the agency may not be able to respond to inquiries until appropriations are enacted. The NIH Clinical Center (the research hospital of NIH) is open. For more details about its operating status, please visit  cc.nih.gov. Updates regarding government operating status and resumption of normal operations can be found at OPM.gov.

Leveraging Pre-trained Models for Machine Learning on Cancer Datasets

Principal Investigator
Name
Daeyoung Hong
Degrees
Ph.D.
Institution
Myongji University
Position Title
Co-Principal Investigator
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-1902
Initial CDAS Request Approval
Apr 30, 2025
Title
Leveraging Pre-trained Models for Machine Learning on Cancer Datasets
Summary
This project aims to investigate the effectiveness of pre-trained machine learning models when applied to cancer datasets. In medical domains annotated data is often limited, making transfer learning a valuable strategy. By utilizing pre-trained models, we aim to evaluate performance improvements in cancer classification tasks.
Aims

- We wish to demonstrate the benefits and limitations of using pre-trained models when applied to cancer datasets.
- We wish to assess fine-tuning strategies to cancer datasets.
- We wish to evaluate how representations learned from general data can be adapted to capture patterns in cancer diagnosis.

Collaborators

Woohwan Jung: Hanyang University