# Examining the Ability of Artificial Neural Networks Machine Learning Models to Accurately Predict Complications Following Posterior Lumbar Spine Fusion

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/examining-the-ability-of-artificial-neural-networks-machine-learning-models-to/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jun Kim,Robert Merrill,Varun Arvind,Deepak Kaji,Sara Pasik,Chuma C. Nwachukwu,Luilly Vargas,Nebiyu Osman,Eric K. Oermann,John M. Caridi,Samuel K. Cho |
| Citations | 212 |
| DOI | 10.1097/brs.0000000000002442 |
| Fields | Engineering,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2762836337 |
| PMID | 29016439 |
| Type | article |
| Year | 2017 |

## Paper authors

- [Jun Kim](https://scholariq.org/researchers/jun-kim/)
- [Samuel K. Cho](https://scholariq.org/researchers/samuel-k-cho/)

## Paper journal

- [Spine](https://scholariq.org/journals/spine/)

## Paper primary topic

- [Spine and Intervertebral Disc Pathology](https://scholariq.org/topics/spine-and-intervertebral-disc-pathology/)

## Paper topics

- [Spine and Intervertebral Disc Pathology](https://scholariq.org/topics/spine-and-intervertebral-disc-pathology/)
- [Medical Imaging and Analysis](https://scholariq.org/topics/medical-imaging-and-analysis/)
- [Sepsis Diagnosis and Treatment](https://scholariq.org/topics/sepsis-diagnosis-and-treatment/)

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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.