# Predicting Postoperative Mortality With Deep Neural Networks and Natural Language Processing: Model Development and Validation

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/predicting-postoperative-mortality-with-deep-neural-networks-and-natural/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Pei‐Fu Chen,Li‐Chin Chen,Yow-Kuan Lin,Guo-Hung Li,Feipei Lai,Cheng-Wei Lü,Chi-Yu Yang,Kuan‐Chih Chen,Tzu‐Yu Lin |
| Citations | 26 |
| DOI | 10.2196/38241 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://medinform.jmir.org/2022/5/e38241/PDF |
| OpenAlex ID | https://openalex.org/W4229455170 |
| PMID | 35536634 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Kuan‐Chih Chen](https://scholariq.org/researchers/kuan-chih-chen/)

## Paper primary topic

- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)

## Paper topics

- [Machine Learning in Healthcare](https://scholariq.org/topics/machine-learning-in-healthcare/)
- [Artificial Intelligence in Healthcare and Education](https://scholariq.org/topics/artificial-intelligence-in-healthcare-and-education/)
- [Cardiac, Anesthesia and Surgical Outcomes](https://scholariq.org/topics/cardiac-anesthesia-and-surgical-outcomes/)

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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.