Mental Health

Artificial Intelligence

We are currently working on many different algorithms to be able to proper support doctors diagnose early stage mental health issues like Burnout, Anxiety and Depression.

It’s estimated that around one billion people globally have a mental or substance use disorder.

Mental health disorders are on the rise in every country in the world and could cost the global economy up to $16 trillion between 2010 and 2030 if a collective failure to respond is not addressed.

The true prevalence of mental health disorders globally remains poorly understood. Diagnosis statistics alone would not bring us close to the true figure — mental health is typically underreported, and under-diagnosed. If relying on mental health diagnoses alone, prevalence figures would be likely to reflect healthcare spending (which allows for more focus on mental health disorders) rather than giving a representative perspective on differences between countries; high-income countries would likely show significantly higher prevalence as a result of more diagnoses.

Some mental health issues resulting directly from technology — addiction, as social media platforms use the same techniques as gambling firms to create psychological dependencies and real imbalance of brain chemicals among teens that resembles depression and anxiety; and smartphone anxiety, including “low-battery anxiety,” “nomophobia”, the fear people can feel when they are out of mobile contact, even FOMO (fear of missing out). The dependency is strong, and globally pervasive and the World Health Organization officially recognizes video game addiction as a mental health disorder.

Here is the true paradigm , we are using technology to combat the tech addiction after all.

We created different types of algorithm to analyze data , videos and speech to find patterns that will allow us to predict early stage patients, more than that to be able to point out best treatment options.

If you are interested to know more about our work, please get in touch.

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