Medical language model specialized in extracting cardiac knowledge

The advent of the Transformer has significantly altered the course of research in Natural Language Processing (NLP) within the domain of deep learning, making Transformer-based studies the mainstream in subsequent NLP research. There has also been considerable advancement in domain-specific NLP rese...

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Veröffentlicht in:Scientific reports 2024-11, Vol.14 (1), p.29059-10, Article 29059
Hauptverfasser: Gwon, Hansle, Seo, Jiahn, Park, Seohyun, Kim, Young-Hak, Jun, Tae Joon
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Sprache:eng
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Zusammenfassung:The advent of the Transformer has significantly altered the course of research in Natural Language Processing (NLP) within the domain of deep learning, making Transformer-based studies the mainstream in subsequent NLP research. There has also been considerable advancement in domain-specific NLP research, including the development of specialized language models for medical. These medical-specific language models were trained on medical data and demonstrated high performance. While these studies have treated the medical field as a single domain, in reality, medical is divided into multiple departments, each requiring a high level of expertise and treated as a unique domain. Recognizing this, our research focuses on constructing a model specialized for cardiology within the medical sector. Our study encompasses the creation of open-source datasets, training, and model evaluation in this nuanced domain.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-80165-z