# Integrating Retrieval-Augmented Generation with Large Language Models in Nephrology: Advancing Practical Applications

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/integrating-retrieval-augmented-generation-with-large-language-models-in/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jing Miao,Charat Thongprayoon,Supawadee Suppadungsuk,Oscar A. Garcia Valencia,Wisit Cheungpasitporn |
| Citations | 157 |
| DOI | 10.3390/medicina60030445 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/1648-9144/60/3/445/pdf?version=1709877206 |
| OpenAlex ID | https://openalex.org/W4392597393 |
| PMID | 38541171 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Wisit Cheungpasitporn](https://scholariq.org/researchers/wisit-cheungpasitporn/)

## Paper journal

- [Medicina](https://scholariq.org/journals/medicina/)

## 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/)
- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

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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.