This paper is in the following e-collection/theme issue:

Natural Language Processing (899) Clinical Information and Decision Making (1890) Precision Medicine (153) Artificial Intelligence (2084) Ontologies, Classifications, and Coding (320)

Published on in Vol 13 (2025)

This is a member publication of University of Manchester (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68558, first published .
Generative Models and Sentence Transformers for the Recognition and Normalization of Continuous and Discontinuous Phenotype Mentions: Model Development and Evaluation

Generative Models and Sentence Transformers for the Recognition and Normalization of Continuous and Discontinuous Phenotype Mentions: Model Development and Evaluation

Generative Models and Sentence Transformers for the Recognition and Normalization of Continuous and Discontinuous Phenotype Mentions: Model Development and Evaluation

Authors of this article:

Areej Alhassan1, 2 Author Orcid Image ;   Viktor Schlegel1, 3 Author Orcid Image ;   Monira Aloud2 Author Orcid Image ;   Riza Batista-Navarro1 Author Orcid Image ;   Goran Nenadic1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Areej Alhassan   1, 2 , MSc ;   Viktor Schlegel   1, 3 , PhD ;   Monira Aloud   2 , PhD ;   Riza Batista-Navarro   1 , PhD ;   Goran Nenadic   1 , PhD

1 Department of Computer Science, School of Engineering, University of Manchester, Manchester, United Kingdom

2 Department of Management Information Systems, College of Business Administration, King Saud University, Riyadh, Saudi Arabia

3 Imperial Global Singapore, Imperial College London, Singapore, Singapore

Corresponding Author: