# 5G-enabled deep learning-based framework for healthcare mining: State of the art and challenges

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/5g-enabled-deep-learning-based-framework-for-healthcare-mining-state-of-the-art/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Rahil Parmar,Dhruval Patel,Naitik Panchal,Uttam Chauhan,Jitendra Bhatia |
| Citations | 5 |
| DOI | 10.1016/b978-0-323-90615-9.00016-5 |
| Fields | Health Professions,Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4285144967 |
| Type | book-chapter |
| Year | 2022 |

## Paper authors

- [Uttam Chauhan](https://scholariq.org/researchers/uttam-chauhan/)

## Paper journal

- [Elsevier eBooks](https://scholariq.org/journals/elsevier-ebooks/)

## Paper primary topic

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

## Paper topics

- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [Artificial Intelligence in Healthcare](https://scholariq.org/topics/artificial-intelligence-in-healthcare/)
- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)

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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.