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

Formative Evaluation of Digital Health Interventions (2415) Natural Language Processing (693)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41137, first published .
Fine-tuning Strategies for Classifying Community-Engaged Research Studies Using Transformer-Based Models: Algorithm Development and Improvement Study

Fine-tuning Strategies for Classifying Community-Engaged Research Studies Using Transformer-Based Models: Algorithm Development and Improvement Study

Fine-tuning Strategies for Classifying Community-Engaged Research Studies Using Transformer-Based Models: Algorithm Development and Improvement Study

Authors of this article:

Brian J Ferrell1 Author Orcid Image
Article Authors Cited by (2) Tweetations (2) Metrics

Journals

  1. Ferrell B, Raskin S, Zimmerman E. Calibrating a Transformer-Based Model’s Confidence on Community-Engaged Research Studies: Decision Support Evaluation Study. JMIR Formative Research 2023;7:e41516 View
  2. Yu S, Yang S, Yoon S. The Design of an Intelligent Lightweight Stock Trading System Using Deep Learning Models: Employing Technical Analysis Methods. Systems 2023;11(9):470 View