Key result
AI-enhanced EEG analysis shows significant publication growth for clinical decision support systems since 2025.
Why the study?
Although AI has transformed EEG analysis, EEG-based clinical decision support systems only recently gained momentum, prompting an examination of timely developments and remaining challenges for clinical adoption.
Despite rapid growth in AI-enhanced EEG research, the translation into clinical decision support systems in neurology faces significant regulatory, interpretability, and integration barriers.
Answers are grounded in this paper and cite their sources.
Barriers urge caution in clinical uptake of AI-EEG decision support; leaves open regulatory, interpretability, and integration challenges for translational research.
Artificial intelligence has transformed electroencephalography (EEG) analysis, with publication activity accelerating markedly since 2015 and again after 2022. This trend is driven by transformer-based architectures, foundation models for biosignals, and increasingly accessible open-source tooling. Yet, EEG-based clinical decision support systems (CDSS) only recently gained momentum. A scientific literature scan indicates a sharp rise in EEG-CDSS publications in 2025. This mini-review highlights the technological, regulatory, and infrastructural developments that now make EEG-based CDSS particularly timely and delineates the remaining challenges for their widespread adoption in clinical neurology.
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Salchow-Hömmen et al. (2025) studied EEG-based clinical decision support systems. AI-enhanced EEG analysis was evaluated on Publications on EEG-CDSS. AI-enhanced EEG analysis has shown a significant increase in publications related to clinical decision support systems since 2025, indicating growing interest and development in this area.
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