# Evaluating the Effectiveness of advanced large language models in medical Knowledge: A Comparative study using Japanese national medical examination

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/evaluating-the-effectiveness-of-advanced-large-language-models-in-medical/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Mingxin Liu,Tsuyoshi Okuhara,Zhehao Dai,Wenbo Huang,Lin Gu,Hiroko Okada,Emi Furukawa,Takahiro Kiuchi |
| Citations | 53 |
| DOI | 10.1016/j.ijmedinf.2024.105673 |
| Fields | Medicine,Social Sciences |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://doi.org/10.1016/j.ijmedinf.2024.105673 |
| OpenAlex ID | https://openalex.org/W4403869417 |
| PMID | 39471700 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Tsuyoshi Okuhara](https://scholariq.org/researchers/tsuyoshi-okuhara/)

## Paper journal

- [International Journal of Medical Informatics](https://scholariq.org/journals/international-journal-of-medical-informatics/)

## Paper primary topic

- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)

## Paper topics

- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [Innovations in Medical Education](https://scholariq.org/topics/innovations-in-medical-education/)
- [Diversity and Career in Medicine](https://scholariq.org/topics/diversity-and-career-in-medicine/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.