Could Artificial Intelligence Improve the Diagnosis of Epilepsy?

Receiving a diagnosis of epilepsy is not always straightforward. While an EEG, or electroencephalogram, is one of the most important tests used to investigate seizures, many people who have epilepsy have a normal EEG between seizures. This can make diagnosis more challenging and can sometimes lead to delays in starting the right treatment.

A recent UK research study involving eight NHS centres and co-authored by Dr Francesco Manfredonia explored whether advanced computer analysis of routine EEG recordings could help identify signs of epilepsy that are not visible to the human eye. The findings offer encouraging possibilities for the future of epilepsy diagnosis.

Why can an EEG be normal?

An EEG records the brain's electrical activity at the time of the test. However, epileptic activity is often intermittent. This means that a person with epilepsy may have a routine EEG that appears completely normal between seizures.

Neurologists may combine EEG findings with:

• A detailed description of the event
• Medical history
• Witness accounts
• Brain imaging such as MRI, when appropriate

Diagnosing epilepsy therefore remains a clinical decision rather than one that relies on a single test.

What did the study investigate?

Researchers analysed more than 800 EEG recordings collected from patients across eight NHS hospitals.

They focused specifically on EEGs that had already been reported as non-contributory, meaning that they did not show obvious abnormalities that would confirm epilepsy.

Using sophisticated computational techniques, the researchers looked for subtle patterns within the EEG signals that cannot usually be detected during routine visual interpretation.

What were the findings?

The study found that computer-based analysis was able to distinguish between patients with epilepsy and those with other conditions better than chance, even when the EEG had previously been reported as normal.

The technology is not yet accurate enough to diagnose epilepsy on its own. However, the results suggest that routine EEG recordings may contain information that could eventually provide additional support to clinicians.

The researchers concluded that this approach could potentially help reduce diagnostic delays and lower the risk of misdiagnosis. Further prospective studies are required before the technology could become part of routine clinical practice.

What could this mean for patients?

For people who have experienced a first seizure or unexplained blackout, these findings are encouraging.

Although the technology is still being evaluated, it represents an interesting step towards improving how epilepsy may be assessed in the future.

The importance of specialist assessment

Even as new technologies emerge, the most important part of diagnosing epilepsy remains a thorough specialist assessment.

An experienced neurologist will consider:

• The symptoms before, during and after an event
• Any witness descriptions
• EEG findings
• MRI scan results, if required
• Other medical conditions that can mimic epilepsy

This comprehensive approach helps ensure that the diagnosis is as accurate as possible and that the most appropriate treatment plan can be considered.

Looking ahead

Artificial intelligence and advanced EEG analysis are opening new possibilities in neurological care. Rather than replacing neurologists, these tools are intended to support clinical decision-making by providing additional information when standard investigations are inconclusive.

As research continues, patients may eventually benefit from earlier diagnoses, more personalised care and greater confidence in the assessment process.

If you have experienced a first seizure or have ongoing episodes that remain unexplained, specialist neurological assessment is an important step towards establishing an accurate diagnosis and appropriate treatment plan.