# Toward expert-level medical question answering with large language models

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/toward-expert-level-medical-question-answering-with-large-language-models/

## Facts

| Field | Value |
| --- | --- |
| Author Names | K. K. Singhal,Tao Tu,Juraj Gottweis,Rory Sayres,Ellery Wulczyn,Mohamed Amin,Le Hou,Kevin Clark,Stephen Pfohl,Heather Cole-Lewis,Darlene Neal,Qazi Mamunur Rashid,Mike Schaekermann,Amy Wang,Dev Dash,Jonathan H. Chen,Nigam H. Shah,Sami Lachgar,P. Mansfield,Sushant Prakash,Bradley Green,Ewa Dominowska,Blaise Agüera y Arcas,Nenad Tomašev,Yun Liu,Renee Wong,Christopher Semturs,S. Sara Mahdavi,Joëlle Barral,Dale R. Webster,Greg S. Corrado,Yossi Matias,Shekoofeh Azizi,Alan Karthikesalingam,Vivek Natarajan |
| Citations | 815 |
| DOI | 10.1038/s41591-024-03423-7 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://www.nature.com/articles/s41591-024-03423-7.pdf |
| OpenAlex ID | https://openalex.org/W4406152279 |
| PMID | 39779926 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Jonathan H. Chen](https://scholariq.org/researchers/jonathan-h-chen/)

## Paper journal

- [Nature Medicine](https://scholariq.org/journals/nature-medicine/)

## Paper primary topic

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)

## Paper topics

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)

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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.