# Deep learning in drug discovery: an integrative review and future challenges

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-in-drug-discovery-an-integrative-review-and-future-challenges/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Heba Askr,Enas Elgeldawi,Heba Aboul Ella,Yaseen A. M. M. Elshaier,Mamdouh M. Gomaa,Aboul Ella Hassanien |
| Citations | 385 |
| DOI | 10.1007/s10462-022-10306-1 |
| Fields | Computer Science,Engineering,Materials Science |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://link.springer.com/content/pdf/10.1007/s10462-022-10306-1.pdf |
| OpenAlex ID | https://openalex.org/W4309490745 |
| PMID | 36415536 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Aboul Ella Hassanien](https://scholariq.org/researchers/aboul-ella-hassanien/)

## Paper journal

- [Artificial Intelligence Review](https://scholariq.org/journals/artificial-intelligence-review/)

## Paper primary topic

- [Computational Drug Discovery Methods](https://scholariq.org/topics/computational-drug-discovery-methods/)

## Paper topics

- [Computational Drug Discovery Methods](https://scholariq.org/topics/computational-drug-discovery-methods/)
- [Machine Learning in Materials Science](https://scholariq.org/topics/machine-learning-in-materials-science/)
- [Innovative Microfluidic and Catalytic Techniques Innovation](https://scholariq.org/topics/innovative-microfluidic-and-catalytic-techniques-innovation/)

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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.