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Artificial intelligence: revolutionizing cardiology with large language models.
Boonstra, Machteld J; Weissenbacher, Davy; Moore, Jason H; Gonzalez-Hernandez, Graciela; Asselbergs, Folkert W.
Affiliation
  • Boonstra MJ; Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, Netherlands.
  • Weissenbacher D; Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Moore JH; Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Gonzalez-Hernandez G; Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Asselbergs FW; Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, Netherlands.
Eur Heart J ; 45(5): 332-345, 2024 Feb 01.
Article in En | MEDLINE | ID: mdl-38170821
ABSTRACT
Natural language processing techniques are having an increasing impact on clinical care from patient, clinician, administrator, and research perspective. Among others are automated generation of clinical notes and discharge letters, medical term coding for billing, medical chatbots both for patients and clinicians, data enrichment in the identification of disease symptoms or diagnosis, cohort selection for clinical trial, and auditing purposes. In the review, an overview of the history in natural language processing techniques developed with brief technical background is presented. Subsequently, the review will discuss implementation strategies of natural language processing tools, thereby specifically focusing on large language models, and conclude with future opportunities in the application of such techniques in the field of cardiology.
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Full text: 1 Database: MEDLINE Main subject: Artificial Intelligence / Cardiology Type of study: Prognostic_studies Limits: Humans Language: En Journal: Eur Heart J / Eur. heart j / European heart journal Year: 2024 Type: Article Affiliation country: Netherlands

Full text: 1 Database: MEDLINE Main subject: Artificial Intelligence / Cardiology Type of study: Prognostic_studies Limits: Humans Language: En Journal: Eur Heart J / Eur. heart j / European heart journal Year: 2024 Type: Article Affiliation country: Netherlands