How to report neurotechnology and artificial intelligence studies in epilepsy: Peer-review-inspired recommendations

The integration of neurotechnology and artificial intelligence (AI) in epilepsy research has led to significant advancements in diagnosis, monitoring, and treatment. However, the impact of these innovations is often diminished by inadequate and inaccurate reporting, limiting their reproducibility and implementation. This study aimed to identify common peer review concerns and develop reporting recommendations specific to neurotechnology and AI studies in epilepsy.

We conducted a qualitative analysis of peer review comments from original research article submissions to Epilepsia Open over a 2-year period (September 2021-August 2023). We selected manuscripts that focused on neurotechnology or AI applications in epilepsy, excluding those using standard clinical technologies or conventional statistical analyses. Reviewer comments were classified using a validated checklist, categorizing issues into themes and subthemes. Based on recurrent peer review concerns, we developed a set of reporting recommendations for neurotechnology and AI studies.

Among 329 manuscripts sent for peer review, 67 were classified as neurotechnology or AI studies and included in the analysis. These studies predominantly involved advanced neuroimaging analysis, advanced electroencephalography (EEG) analysis, and neuromodulation systems. Reviewer comments were primarily focused on study methodology (37%), manuscript presentation (19%), discussion (17%), and results (12%). Based on peer review comments, we formulated reporting recommendations, hoping to enhance study transparency, methodological rigor, and reproducibility.

Our reporting recommendations address key concerns raised during peer review, providing guidance to authors and reviewers to improve the quality and clarity of neurotechnology and AI research in epilepsy. These recommendations complement existing reporting standards and contribute to the advancement of robust and impactful research in the field.

We studied how researchers report studies on neurotechnology and AI in epilepsy. Many studies face problems during peer review, such as unclear methods, weak study rationale, and errors in statistics or citations. We analyzed reviewer feedback and created recommendations to improve how these studies are reported. Our goal is to help researchers develop and present their work more clearly and accurately, making it easier for others to understand and build upon their findings. This can lead to better use of AI and neurotechnology in epilepsy research and care.