# Intelligent Machine Learning Approach for Effective Recognition of Diabetes in E-Healthcare Using Clinical Data

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/intelligent-machine-learning-approach-for-effective-recognition-of-diabetes-in-e/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Amin Ul Haq,Jianping Li,Jalaluddin Khan,Muhammad Hammad Memon,Shah Nazir,Sultan Ahmad,Ghufran Ahmad Khan,Amjad Ali |
| Citations | 156 |
| DOI | 10.3390/s20092649 |
| Fields | Computer Science,Health Professions,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/1424-8220/20/9/2649/pdf?version=1588989216 |
| OpenAlex ID | https://openalex.org/W3021382697 |
| PMID | 32384737 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Jianping Li](https://scholariq.org/researchers/jianping-li/)

## Paper journal

- [Sensors](https://scholariq.org/journals/sensors/)

## 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/)
- [Imbalanced Data Classification Techniques](https://scholariq.org/topics/imbalanced-data-classification-techniques/)
- [Traditional Chinese Medicine Studies](https://scholariq.org/topics/traditional-chinese-medicine-studies/)

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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.