# Alzheimer's disease detection using depthwise separable convolutional neural networks

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/alzheimer-s-disease-detection-using-depthwise-separable-convolutional-neural/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Junxiu Liu,Mingxing Li,Yuling Luo,Su Yang,Wei Li,Yifei Bi |
| Citations | 162 |
| DOI | 10.1016/j.cmpb.2021.106032 |
| Fields | Computer Science,Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3134726279 |
| PMID | 33713959 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Su Yang](https://scholariq.org/researchers/su-yang/)

## Paper journal

- [Computer Methods and Programs in Biomedicine](https://scholariq.org/journals/computer-methods-and-programs-in-biomedicine/)

## Paper primary topic

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)

## Paper topics

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)
- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)
- [Dementia and Cognitive Impairment Research](https://scholariq.org/topics/dementia-and-cognitive-impairment-research/)

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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.