Neuroimage analysis using artificial intelligence approaches: a systematic review

Eric Jacob Bacon,Dianning He, N’bognon Angèle D’avilla Achi,Lanbo Wang,Han Li, Patrick Dê Zélèman Yao-Digba,Patrice Monkam,Shouliang Qi

Medical & Biological Engineering & Computing(2024)

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摘要
In the contemporary era, artificial intelligence (AI) has undergone a transformative evolution, exerting a profound influence on neuroimaging data analysis. This development has significantly elevated our comprehension of intricate brain functions. This study investigates the ramifications of employing AI techniques on neuroimaging data, with a specific objective to improve diagnostic capabilities and contribute to the overall progress of the field. A systematic search was conducted in prominent scientific databases, including PubMed, IEEE Xplore, and Scopus, meticulously curating 456 relevant articles on AI-driven neuroimaging analysis spanning from 2013 to 2023. To maintain rigor and credibility, stringent inclusion criteria, quality assessments, and precise data extraction protocols were consistently enforced throughout this review. Following a rigorous selection process, 104 studies were selected for review, focusing on diverse neuroimaging modalities with an emphasis on mental and neurological disorders. Among these, 19.2
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关键词
Neuroimaging,Artificial intelligence,Machine learning,Deep learning,Mental illness,Neurological disease
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