Recent advancements in neurosurgical techniques have focused on integrating innovative technologies to enhance patient outcomes and improve diagnostic capabilities. One notable study demonstrated that adapted large language models (LLMs) can outperform medical experts in clinical text summarization, significantly alleviating the burden on clinicians by efficiently analyzing and summarizing vast amounts of data from electronic health records (ref: Van Veen doi.org/10.1038/s41591-024-02855-5/). This highlights the potential of artificial intelligence in streamlining clinical workflows. Additionally, the development of soft neural probes, which are integrated through high-resolution printing of liquid electronics on the cranium, has shown promise in long-term neural activity recording. In-vivo studies indicated that these probes could record neural activities for up to 33 weeks, providing a novel approach to studying brain functions without the constraints of bulky electronics (ref: Park doi.org/10.1038/s41467-024-45768-0/). Furthermore, the application of a genetic risk score model has improved the prediction of multiple sclerosis diagnoses in patients presenting with optic neuritis, emphasizing the importance of genetic factors in clinical decision-making (ref: Loginovic doi.org/10.1038/s41467-024-44917-9/).