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 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.

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Publication Details

Journal
Scientific Reports
Published
2024-11-23
DOI
https://doi.org/10.1038/s41598-024-80165-z
Citations
2
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.69

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article

Medical language model specialized in extracting cardiac knowledge

Young‐Hak Kim, Hyeram Seo, Hansle Gwon, Tae Joon Jun et al.
2 citations
Scientific Reports
Topic Modeling
0.69
article

Medical language model specialized in extracting cardiac knowledge

Young‐Hak Kim, Hyeram Seo, Hansle Gwon, Tae Joon Jun, Seohyun Park
article en
2 citations

Abstract

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.

Scientific ReportsVol. 14(1)
Ulsan College (KR), Asan Medical Center (KR), University of Ulsan (KR)
Korea Health Industry Development Institute
Quality Education
Openalex Percentile: Top 23%
Topic Modeling
0.69
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