# Predicting prognostic factors in kidney transplantation using a machine learning approach to enhance outcome predictions: a retrospective cohort study

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/predicting-prognostic-factors-in-kidney-transplantation-using-a-machine-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jin-Myung Kim,HyoJe Jung,Hye Eun Kwon,Youngmin Ko,Joo Hee Jung,Hyunwook Kwon,Young Hoon Kim,Tae Joon Jun,Sang‐Hyun Hwang,Sung Shin |
| Citations | 13 |
| DOI | 10.1097/js9.0000000000002028 |
| Fields | Health Professions,Medicine |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://doi.org/10.1097/js9.0000000000002028 |
| OpenAlex ID | https://openalex.org/W4401409485 |
| PMID | 39116448 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Hye Eun Kwon](https://scholariq.org/researchers/hye-eun-kwon/)

## Paper journal

- [International Journal of Surgery](https://scholariq.org/journals/international-journal-of-surgery/)

## Paper primary topic

- [Renal Transplantation Outcomes and Treatments](https://scholariq.org/topics/renal-transplantation-outcomes-and-treatments/)

## Paper topics

- [Renal Transplantation Outcomes and Treatments](https://scholariq.org/topics/renal-transplantation-outcomes-and-treatments/)
- [Renal and Vascular Pathologies](https://scholariq.org/topics/renal-and-vascular-pathologies/)
- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-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.