📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis. (2016)

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.17863/cam.15641

Publication URI: https://www.repository.cam.ac.uk/handle/1810/269419

Type: Journal Article/Review