Using Artificial intelligence to diagnose brain disorders

Elminda, an Israeli company, developed an innovative solution for assessing the health state of the brain based on electroencephalography and artificial intelligence.

The system, called Brain Network Analytics (BNA), records the cerebral response of patients through electrodes placed on the head while they perform a series of tasks with a computer.

The system analyzes electroencephalograms using advanced algorithms, including digital signal processing, chart theory, clustering analysis and compares their patterns with those of a reference database of over 450,000 healthy subjects.

The results – which are available within one hour after the test – provide unique insights into the patient’s brain function and dysfunction regarding various cognitive domains (e.g. working memory, attention, sensory process, and motor control), allowing diagnosis and monitoring of healthy patients as well as of those suffering from brain-related disorders (e.g. depression, Alzheimer’s disease, traumatic brain injury, and Parkinson’s disease).

Compared to existing brain health assessment tools, the Elminda test takes less than 30 minutes and can be conducted by anyone trained in the system. This is fully portable, can be installed in less than three hours and is suitable for most operating rooms.

In addition to its brain health programme, Elminda is also investigating BNA-based markers (neuromarkers) to enable diagnostics, monitoring, and treatment outcome prediction for numerous brain-related disorders. Under this framework, Elminda has developed the PREDICT tool, a novel screening solution for physicians with the intended use of supporting and optimising treatment decisions for patients with depression.

Each year, about 7% of the population suffer from depression, equivalent to almost 53 million people in Europe alone.

Large numbers of antidepressants from various classes are available for treating depression, including selective serotonin reuptake inhibitors (SSRI), serotonin–norepinephrine reuptake inhibitor (SNRI), and tricyclic antidepressants (TCAs). However, only 25-50% of patients respond to an initial course of antidepressant therapy.

Finding an adequate antidepression treatment is done empirically via trial and error (medication switches, combinations, adjunctive therapy with mood stabilisers, benzodiazepines, atypical antipsychotics and other agents). It can take over 12 months to find the right treatment and, in 32% of cases, there is no response to any drug therapy.

Transcranial magnetic stimulation (TMS) is a non-invasive procedure that uses magnetic fields to modulate activity in discrete cortical regions (i.e. neurostimulation). TMS has therapeutic efficacy for various neuropsychiatric disorders, including depression.

However, TMS is an expensive procedure that is only effective in 30-50% of patients treated. It is also a treatment that lasts 4-6 weeks with sessions five days a week, each taking between 20-30 minutes.

PREDICT is an electroencephalogram (EEG) based screening software that predicts reactivity to both antidepressants and TMS treatment, allowing you to treat your patient with optimized treatments based on validated brain biomarkers.

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