Deep Learning-Enhanced Internet of Medical Things to Analyze Brain CT Scans of Hemorrhagic Stroke Patients: A New Approach

Author:

Xu Yongzhao,Holanda Gabriel,Souza Luis Fabricio. de F.ORCID,Silva Hercules,Gomes AdriellORCID,Silva Iagson,Ferreira Marcos,Jia Chuanyu,Han TaoORCID,de Albuquerque Victor Hugo C.ORCID,Filho Pedro P. ReboucasORCID

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001

Brazilian National Council for Research and Development

National Natural Science Foundation of China

Dongguan core technology frontier project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Cited by 38 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Hybrid Ensemble Deep Learning Model for Advancing Ischemic Brain Stroke Detection and Classification in Clinical Application;Journal of Imaging;2024-07-02

2. A comprehensive review and experimental comparison of deep learning methods for automated hemorrhage detection;Engineering Applications of Artificial Intelligence;2024-07

3. Application of Machine Learning in Identifying Brain Strokes;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

4. Feature Fusion-based Brain Stroke Identification Model Using Computed Tomography Images;Journal of Disability Research;2024-05-22

5. Enhanced UNet Approach for Detecting Stroke Lesions in Computed Tomography Brain Scans;2024 IEEE 4th International Conference on Smart Information Systems and Technologies (SIST);2024-05-15

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