Unveiling Medical Insights: Advanced Topic Extraction from Scientific Articles...Medical Informatics Europe (MIE) 34th Conference, August 25–29, 2024, Athens, Greece.
In the ever-evolving landscape of medical research and healthcare, the abundance of scientific articles presents both a treasure trove of knowledge and a daunting challenge. Researchers, clinicians, and data scientists grapple with vast amounts of unstructured information, seeking to extract meaning...
| Publicado en: | Studies in Health Technology & Informatics Vol. 316; pp. 944 - 949 |
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| Autores principales: | , , , |
| Formato: | proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | In the ever-evolving landscape of medical research and healthcare, the abundance of scientific articles presents both a treasure trove of knowledge and a daunting challenge. Researchers, clinicians, and data scientists grapple with vast amounts of unstructured information, seeking to extract meaningful insights that can drive advancements in the biomedical domain including, research trends, patient care, drug discovery, and disease understanding. This paper utilizes the topic extraction algorithms on Breast Cancer Research to shed light on the current trends and the path to follow in this field. We utilized TextRank and Large Language Models (LLM) using the TripleA tool to extract topics in the field, analyzing and comparing the results. |
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