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.

Principal Investigator
Name
Rafael Berlanga
Degrees
PhD.
Institution
Universitat Jaume I
Position Title
Full-time professor
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-370
Initial CDAS Request Approval
Nov 6, 2017
Title
Early detection of lung cancer with deep learning and graph databases
Summary
In this investigation, we propose a new approach that combines deep learning mix with a knowledge graph database.The knowledge graph aims at representing as a graph all relevant information around lung cancer such as symptoms, anatomical details, etc. In a second step, by using this graph, we will select subsets of images with the aim of training neural network models that help early lung cancer detection.
Aims

To improve current DL approaches on Radiography with proper examples for training.
To represent all relevant information related to decision support into a knowledge graph.

Collaborators

ActualMed, a company that manages RIS/PACS systems in the cloud (http://www.actualmed.com/)