# Calibration drift in regression and machine learning models for acute kidney injury

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/calibration-drift-in-regression-and-machine-learning-models-for-acute-kidney/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sharon E. Davis,Thomas A. Lasko,Guanhua Chen,Edward D Siew,Michael E. Matheny |
| Citations | 298 |
| DOI | 10.1093/jamia/ocx030 |
| Fields | Medicine |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://academic.oup.com/jamia/article-pdf/24/6/1052/25421982/ocx030.pdf |
| OpenAlex ID | https://openalex.org/W2604834158 |
| PMID | 28379439 |
| Type | article |
| Year | 2017 |

## Paper authors

- [Guanhua Chen](https://scholariq.org/researchers/guanhua-chen/)

## Paper journal

- [Journal of the American Medical Informatics Association](https://scholariq.org/journals/journal-of-the-american-medical-informatics-association/)

## Paper primary topic

- [Acute Kidney Injury Research](https://scholariq.org/topics/acute-kidney-injury-research/)

## Paper topics

- [Acute Kidney Injury Research](https://scholariq.org/topics/acute-kidney-injury-research/)
- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)
- [Chronic Kidney Disease and Diabetes](https://scholariq.org/topics/chronic-kidney-disease-and-diabetes/)

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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.