How Can Transformer Models Shape Future Healthcare: A Qualitative Study.
Stud Health Technol Inform
; 309: 43-47, 2023 Oct 20.
Article
em En
| MEDLINE
| ID: mdl-37869803
ABSTRACT
Transformer models have been successfully applied to various natural language processing and machine translation tasks in recent years, e.g. automatic language understanding. With the advent of more efficient and reliable models (e.g. GPT-3), there is a growing potential for automating time-consuming tasks that could be of particular benefit in healthcare to improve clinical outcomes. This paper aims at summarizing potential use cases of transformer models for future healthcare applications. Precisely, we conducted a survey asking experts on their ideas and reflections for future use cases. We received 28 responses, analyzed using an adapted thematic analysis. Overall, 8 use case categories were identified including documentation and clinical coding, workflow and healthcare services, decision support, knowledge management, interaction support, patient education, health management, and public health monitoring. Future research should consider developing and testing the application of transformer models for such use cases.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Codificação Clínica
/
Instalações de Saúde
Limite:
Humans
Idioma:
En
Revista:
Stud Health Technol Inform
Assunto da revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Suíça