Background/Objectives: Artificial intelligence (AI), particularly large language models (LLMs), has demonstrated versatility in various applications but faces challenges in specialized domains like neurology. This study evaluates a specialized LLM’s capability and trustworthiness in complex neurological diagnosis, comparing its performance to neurologists in simulated clinical settings. Methods: We deployed GPT-4 Turbo (OpenAI, San Francisco, CA, US) through Neura (Sciense, New York, NY, US), an AI infrastructure with a dual-database architecture integrating “long-term memory” and “short-term memory” components on a curated neurological corpus. Five representative clinical scenarios were presented to 13 neurologists and the AI system. Participants formulated differential diagnoses based on initial presentations, followed by definitive diagnoses after receiving conclusive clinical information. Two senior academic neurologists blindly evaluated all responses, while an independent investigator assessed the verifiability of AI-generated information. Results: AI achieved a significantly higher normalized score (86.17%) compared to neurologists (55.11%, p < 0.001). For differential diagnosis questions, AI scored 85% versus 46.15% for neurologists, and for final diagnosis, 88.24% versus 70.93%. AI obtained 15 maximum scores in its 20 evaluations and responded in under 30 s compared to neurologists’ average of 9 min. All AI-provided references were classified as relevant with no hallucinatory content detected. Conclusions: A specialized LLM demonstrated superior diagnostic performance compared to practicing neurologists across complex clinical challenges. This indicates that appropriately harnessed LLMs with curated knowledge bases can achieve domain-specific relevance in complex clinical disciplines, suggesting potential for AI as a time-efficient asset in clinical practice.

Objective: Our objective was to evaluate the relationship between scalp‐EEG and stereoelectroencephalography (SEEG) seizure‐onset patterns (SOP) in patients with MRI‐negative drug‐resistant focal epilepsy.Methods: We analyzed retrospectively 41 patients without visible lesion on brain MRI who underwent video‐EEG followed by SEEG. We defined five types of SOPs on scalp‐EEG and eight types on SEEG. We examined how various clinical variables affected scalp‐EEG SOPs.Results: The most prevalent scalp SOPs were rhythmic sinusoidal activity (56.8%), repetitive epileptiform discharges (22.7%), and paroxysmal fast activity (15.9%). The presence of paroxysmal fast activity on scalp‐EEG was always seen without delay from clinical onset and correlated with the presence of low‐voltage fast activity in SEEG (sensitivity = 22.6%, specificity = 100%). The main factor explaining the discrepancy between the scalp and SEEG SOPs was the delay between clinical and scalp‐EEG onset. There was a correlation between the scalp and SEEG SOPs when the scalp onset was simultaneous with the clinical onset (p = 0.026). A significant delay between clinical and scalp discharge onset was observed in 25% of patients and featured always with a rhythmic sinusoidal activity on scalp, corresponding to similar morphology of the discharge on SEEG. The presence of repetitive epileptiform discharges on scalp was associated with an underlying focal cortical dysplasia (sensitivity = 30%, specificity = 90%). There was no significant association between the scalp SOP and the epileptogenic zone location (deep or superficial), or surgical outcome.Significance: In patients with MRI‐negative focal epilepsy, scalp SOP could suggest the SEEG SOP and some etiology (focal cortical dysplasia) but has no correlation with surgical prognosis. Scalp SOP correlates with the SEEG SOP in cases of simultaneous EEG and clinical onset; otherwise, scalp SOP reflects the propagation of the SEEG discharge.Plain Language Summary: We looked at the correspondence between the electrical activity recorded during the start of focal seizure using scalp and intracerebral electrodes in patients with no visible lesion on MRI. If there is a fast activity on scalp, it reflects similar activity inside the brain. We found a good correspondence between scalp and intracerebral electrical activity for cases without significant delay between clinical and scalp electrical onset (seen in 75% of the cases we studied). Visualizing repetitive epileptic activity on scalp could suggest a particular cause of the epilepsy: a subtype of brain malformation called focal cortical dysplasia.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment yet are increasingly associated with neurological immune-related adverse events (n-irAEs), which can affect any part of the nervous system. Accurate diagnosis is often challenging due to overlapping features with classical paraneoplastic neurological syndromes (PNS) and autoimmune encephalitis (AE). They may also resemble other neurological conditions, including demyelinating diseases. In this review, we present four illustrative cases of post-ICI n-irAEs involving the central nervous system (CNS). Through these cases and accompanying commentaries providing a critical appraisal of the current literature, we highlight the diagnostic, therapeutic, and prognostic challenges associated with these presentations. We emphasize both the role and limitations of neuronal antibody testing. This review stresses the need for rigorous clinical phenotyping, comprehensive immunological screening, and multidisciplinary management to improve early recognition of these complex and often severe complications and guide future therapeutic strategies.

Vagus nerve stimulation (VNS) is an effective neuromodulatory treatment for patients with drug resistant epilepsy who cannot undergo curative surgical resection. Safety information states that the use of radiofrequency ablation devices may damage the VNS generator and leads. However, documented cases are scarce. This 62-year-old patient with bitemporal lobe epilepsy treated with VNS underwent radiofrequency ablation of an atrial fibrillation without any perioperative or postoperative complications.