Uso de Inteligência Artificial na detecção e mapeamento de Acidente Vascular Cerebral (AVC): Uma revisão sistemática da Literatura
Resumo
O acidente vascular cerebral (AVC) é uma das principais causas de mortalidade e incapacidade, exigindo diagnóstico rápido para minimizar danos neurológicos. Este estudo analisa pesquisas recentes que utilizam técnicas de Inteligência Artificial (IA) na detecção e segmentação de lesões isquêmicas e hemorrágicas em exames de tomografia computadorizada (CT) e ressonância magnética (MRI). A revisão foi realizada nas bases PubMed, IEEE Xplore e Scopus, totalizando 27 artigos com modelos como CNNs, U-Net, DenseNet e Vision Transformers. Os resultados indicam que a IA pode aumentar a acurácia diagnóstica e reduzir o tempo de processamento. No entanto, ainda são necessárias validações clínicas e maior integração aos fluxos hospitalares.Referências
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AVANEESH, C.; GOUD, P. R. K. (2025). Ai-driven multimodal prognosis in stroke: integrating neuroimaging and longitudinal clinical data. In 2025 International Conference on Biomedical Engineering, Genebra. IEEE.
AYESHA, N.; SHESHADRI, H. S. (2024). Deep learning technique for detecting and analysing ischemic stroke using mri images. In 2024 IEEE ICDCOT, Genebra. IEEE.
BOJSEN, J. A. e. a. (2024). Artificial intelligence for mri stroke detection: a systematic review and meta-analysis. Insights into Imaging, 15:160.
CHOI, Y.-A. e. a. (2021). Deep learning-based stroke disease prediction system using real-time bio signals. Sensors, 21(13):4269.
EL-SHEIKH, M. M. e. a. (2024). Enhancing acute ischemic stroke diagnosis using iomt and deep learning technologies. Technical report, Galala University, Cairo, Egito.
GNANABASKARAN, A. e. a. (2025). An intelligent framework for early detection of brain strokes using vgg16 and svm. In 2025 IEEE ICECCC, Genebra. IEEE.
HUANG, R. (2024). Leveraging cnn for automated lesion detection in stroke mri scans. In 2024 IEEE ICCC, Genebra. IEEE.
KHALIQ, A. e. a. (2025). Ai-powered medical diagnosis: Vision transformers and perceiver io for multi-disease detection. Computational Biology and Chemistry, page 108586.
LEE, K.-Y. e. a. (2023). Automatic detection and vascular territory classification of hyperacute staged ischemic stroke. Scientific Reports, 13:404.
LIU, K.; YIN, M. C. Z. (2022). Research and application advances in rehabilitation assessment of stroke. Journal of Zhejiang University. Science B, 23(8).
NAIK, Y.; VIDYASAGAR, K. B. (2025). Early detection of brain strokes from mr images using a customized cnn. In 2025 IEEE ICDSIS, Genebra. IEEE.
ORGANIZAÇÃO MUNDIAL DA SAÚDE (2025). Global health estimates.
PATIL, A.; GOVINDARAJ, S. (2023). An ai enabled framework for mri-based data analytics for efficient brain stroke detection. In 2023 IEEE ACCAI, Genebra. IEEE.
PRATHIMA, C. e. a. (2025). A novel approach for early brain stroke detection using genetic algorithm. In 2025 IEEE ICDT, Genebra. IEEE.
SANTOS, L. E. S. (2024). Protocolo rsl: uso de inteligência artificial na detecção e mapeamento de avc. Documento de protocolo.
SHETH, S. A. e. a. (2023). Machine learning and acute stroke imaging. Journal of NeuroInterventional Surgery, 15(2).
SHOKRI, M. J. e. a. (2024). Decoding stroke patterns: a novel deep learning approach to atrial fibrillation risk stratification. In 2024 IEEE DICTA, Genebra. IEEE.
SINHA, S. e. a. (2024). Enigmanet: a novel attention-enhanced segmentation framework for ischemic stroke lesion detection in brain mri. IEEE Access, 12.
SOBHANA, M. e. a. (2025). Edge computing for brain stroke detection using deep learning techniques. In 2025 IEEE ICOECA, Genebra. IEEE.
SUREKHA, Y. e. a. (2025). Advanced stroke prediction leveraging mri data with an ensemble cnn framework. In 2025 IEEE ICOECA, Genebra. IEEE.
TAN, K.; MARVELL, Y. A. (2023). Early ischemic stroke detection using deep learning: a slr. In 2023 IEEE iSemantic, Genebra. IEEE.
VARSHITH, S. V. e. a. (2025). Brain stroke detection using densenet algorithm. In 2025 IEEE GINOTECH, Genebra. IEEE.
VICKRAM, A. S.; SOWNDHARYA, B. B. (2025). Mri slice assisted ischemic-stroke detection using deep-learning scheme. In 2025 IEEE ICEARS, Genebra. IEEE.
VISWAPRIYA, S. E.; RAJESWARI, D. (2024). Attentive feature segmentation model for stroke detection on mri images. In 2024 IEEE BITCON, Genebra. IEEE.
XUE, X. e. a. (2025). An efficient deep learning network for brain stroke detection using salp shuffled shepherded optimization. Scientific Reports, 15:33516.
YADAV, P. K. e. a. (2023). Mri based automatic brain stroke detection using cnn models improved with model scaling. In 2023 IEEE ICPCSN, Genebra. IEEE.
AVANEESH, C.; GOUD, P. R. K. (2025). Ai-driven multimodal prognosis in stroke: integrating neuroimaging and longitudinal clinical data. In 2025 International Conference on Biomedical Engineering, Genebra. IEEE.
AYESHA, N.; SHESHADRI, H. S. (2024). Deep learning technique for detecting and analysing ischemic stroke using mri images. In 2024 IEEE ICDCOT, Genebra. IEEE.
BOJSEN, J. A. e. a. (2024). Artificial intelligence for mri stroke detection: a systematic review and meta-analysis. Insights into Imaging, 15:160.
CHOI, Y.-A. e. a. (2021). Deep learning-based stroke disease prediction system using real-time bio signals. Sensors, 21(13):4269.
EL-SHEIKH, M. M. e. a. (2024). Enhancing acute ischemic stroke diagnosis using iomt and deep learning technologies. Technical report, Galala University, Cairo, Egito.
GNANABASKARAN, A. e. a. (2025). An intelligent framework for early detection of brain strokes using vgg16 and svm. In 2025 IEEE ICECCC, Genebra. IEEE.
HUANG, R. (2024). Leveraging cnn for automated lesion detection in stroke mri scans. In 2024 IEEE ICCC, Genebra. IEEE.
KHALIQ, A. e. a. (2025). Ai-powered medical diagnosis: Vision transformers and perceiver io for multi-disease detection. Computational Biology and Chemistry, page 108586.
LEE, K.-Y. e. a. (2023). Automatic detection and vascular territory classification of hyperacute staged ischemic stroke. Scientific Reports, 13:404.
LIU, K.; YIN, M. C. Z. (2022). Research and application advances in rehabilitation assessment of stroke. Journal of Zhejiang University. Science B, 23(8).
NAIK, Y.; VIDYASAGAR, K. B. (2025). Early detection of brain strokes from mr images using a customized cnn. In 2025 IEEE ICDSIS, Genebra. IEEE.
ORGANIZAÇÃO MUNDIAL DA SAÚDE (2025). Global health estimates.
PATIL, A.; GOVINDARAJ, S. (2023). An ai enabled framework for mri-based data analytics for efficient brain stroke detection. In 2023 IEEE ACCAI, Genebra. IEEE.
PRATHIMA, C. e. a. (2025). A novel approach for early brain stroke detection using genetic algorithm. In 2025 IEEE ICDT, Genebra. IEEE.
SANTOS, L. E. S. (2024). Protocolo rsl: uso de inteligência artificial na detecção e mapeamento de avc. Documento de protocolo.
SHETH, S. A. e. a. (2023). Machine learning and acute stroke imaging. Journal of NeuroInterventional Surgery, 15(2).
SHOKRI, M. J. e. a. (2024). Decoding stroke patterns: a novel deep learning approach to atrial fibrillation risk stratification. In 2024 IEEE DICTA, Genebra. IEEE.
SINHA, S. e. a. (2024). Enigmanet: a novel attention-enhanced segmentation framework for ischemic stroke lesion detection in brain mri. IEEE Access, 12.
SOBHANA, M. e. a. (2025). Edge computing for brain stroke detection using deep learning techniques. In 2025 IEEE ICOECA, Genebra. IEEE.
SUREKHA, Y. e. a. (2025). Advanced stroke prediction leveraging mri data with an ensemble cnn framework. In 2025 IEEE ICOECA, Genebra. IEEE.
TAN, K.; MARVELL, Y. A. (2023). Early ischemic stroke detection using deep learning: a slr. In 2023 IEEE iSemantic, Genebra. IEEE.
VARSHITH, S. V. e. a. (2025). Brain stroke detection using densenet algorithm. In 2025 IEEE GINOTECH, Genebra. IEEE.
VICKRAM, A. S.; SOWNDHARYA, B. B. (2025). Mri slice assisted ischemic-stroke detection using deep-learning scheme. In 2025 IEEE ICEARS, Genebra. IEEE.
VISWAPRIYA, S. E.; RAJESWARI, D. (2024). Attentive feature segmentation model for stroke detection on mri images. In 2024 IEEE BITCON, Genebra. IEEE.
XUE, X. e. a. (2025). An efficient deep learning network for brain stroke detection using salp shuffled shepherded optimization. Scientific Reports, 15:33516.
YADAV, P. K. e. a. (2023). Mri based automatic brain stroke detection using cnn models improved with model scaling. In 2023 IEEE ICPCSN, Genebra. IEEE.
Publicado
19/07/2026
Como Citar
SANTOS, Lara Emanuelly da Silva.
Uso de Inteligência Artificial na detecção e mapeamento de Acidente Vascular Cerebral (AVC): Uma revisão sistemática da Literatura. In: ENCONTRO NACIONAL DE COMPUTAÇÃO DOS INSTITUTOS FEDERAIS (ENCOMPIF), 13. , 2026, Gramado/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 113-120.
ISSN 2763-8766.
DOI: https://doi.org/10.5753/encompif.2026.22623.
