# Artificial intelligence predicts the progression of diabetic kidney disease using big data machine learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/artificial-intelligence-predicts-the-progression-of-diabetic-kidney-disease/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Masaki Makino,Ryo Yoshimoto,Masaki Ono,Toshinari Itoko,Takayuki Katsuki,Akira Koseki,Michiharu Kudo,Kyoichi Haida,Jun Kuroda,Ryosuke Yanagiya,Eiichi Saitoh,Kiyotaka Hoshinaga,Yukio Yuzawa,Atsushi Suzuki |
| Citations | 259 |
| DOI | 10.1038/s41598-019-48263-5 |
| Fields | Computer Science,Health Professions,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.nature.com/articles/s41598-019-48263-5.pdf |
| OpenAlex ID | https://openalex.org/W2968847082 |
| PMID | 31413285 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Yukio Yuzawa](https://scholariq.org/researchers/yukio-yuzawa/)

## Paper journal

- [Scientific Reports](https://scholariq.org/journals/scientific-reports/)

## Paper primary topic

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

## Paper topics

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

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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.