How artificial intelligence could aid mental health
Advances in technology and computing systems today seem to point the future of psychiatry in one direction. So many of us willingly document the inner workings of our lives online leaving a wealth of data out there that could aid mental health monitoring.
When it comes to machine learning, algorithms, if administered effectively could not only improve predictive accuracy aimed at harmful thoughts and behaviours, but they could identify potential risk factors and then advise treatment plans to combat them.
Cognitive systems that analyse speech, body language and writing could all be indicators that help detect underlying conditions or flag warnings to medical professionals. One company that uses data from such systems is IBM. Scientists are harnessing machine learning to monitor transcripts and audio from psychiatric interviews.
This can help clinicians spot patterns in speech to accurately predict and monitor psychological behaviours. The ongoing observations conducted with this data are improving healthcare as we know it, positioning professionals to care for patients more effectively.
‘Today it only takes about 300 words to help clinicians predict the probability of psychosis in a user.’ – IBM
According to American Well, 75% of millennials would use telehealth for behavioural health. Teladoc is just one of several prominent companies aiming to connect patients to physicians, paediatricians and behavioural therapists 24/7, 365 days of the year.
In the UK, suicide is the leading cause of death in men aged between 20 and 40. As detailed in Yuval Noah Harari’s book Homo Deus, more people die from suicide now than all acts of violence (crime, war and terrorism) put together.
“Alexa, start my therapy session”
A recent study performed by the World Health Organisation (WHO) revealed it is estimated that on a global scale, at least one person dies every 40 seconds as a result of poor mental health. Suggestively, there is still a wealth of work that must be done to provide those that suffer with better means of treatment and access to assisted services.
Whilst it could be argued that a large proportion of consumers are yet to adapt to the concept of a smart speaker within their homes, 26.2% (66.4 million) of the U.S. adult population alone are now reported to own a voice-activated device as outlined in a recent report by Voicebot.
Reflecting on #WorldMentalAwarenessHealthWeek, we dug deep into how applications of machine learning are being utilised to provide health benefits for users of smart devices.
5 Tech Companies and Apps Improving Mental Health
David Plans, Chief Science Officer and founder of London based company BioBeats combines big data and artificial intelligence. The company aims to provide users with access to their real-time health data. The software takes measurements such as heart rate variability, brain function, sleep and activity levels via wearable smart devices.
The software application BioBase, aims to promote mental wellbeing by identifying the causes of stress to better understand how to cope with, control and reduce it. A near-death experience related to mental exhaustion led Plans to provide a solution which would prevent others from encounters of a similar nature.
Youper is an app that uses ‘artificial intelligence to empower people to pursue happiness’. This AI assistant can help those suffering with anxiety or depression, or simply help improve productivity and creativity.
The combined skills of CEO Dr Jose Hamilton and co-founders Diego Dotta Couto and Thiago Marafon have built this AI on techniques used in Cognitive Behavioural Therapy, Acceptance and Commitment Therapy and Mindfulness and Meditation.
To date, Youper has analysed anonymous mental health data from one million people and discovered that 80% of those users saw improved moods by talking to the app. A further 83% experience a reduction in negative moods after just one conversation – with the average chat length required to induce positive change being just 7 minutes.
3. Vanderbilt University Medical Centre
In 2017, a group of data scientists at the Vanderbilt University Medical Centre in Nashville created a machine learning algorithm that uses hospital admissions data to predict the likelihood of any given individual taking their own life.
The trials gathered data from over 5000 patients admitted to the hospital for mental health related incidences and revealed that the algorithm was 84% accurate at predicting whether someone would commit suicide within the next week. It was also 80% accurate at predicting the likelihood of a suicide attempt within a two-year time span!
This technology could be ground-breaking in helping save lives across the globe, but the risks of safely handling sensitive patient data could cause controversy. This research could be worth getting on board with though – according to WHO nearly two-thirds of people with a known mental disorder never seek help from a health professional.
The app nOCD was built after several team members struggled immensely with Obsessive-Compulsive Disorder. Described by one user as having a ‘mini therapist in your pocket’, the app aims to assist OCD sufferers at any stage in their journey – whether it’s used for education or recovery.
Chief Medical officer at nOCD Dr Jamie Feusner conducted research from anonymous data collected within the app. An ad hoc dataset of obsession-related words were analysed through natural language processing.
The results show that Harm OCD is the most pervasive type of OCD, being 66% more common than contamination fears. This app creates potential for machine learning and AI, collecting valuable data points that help better understand psychiatric conditions.
5. SilverCloud Health
Boston based company SilverCloud Health has partnered with Microsoft Labs in Cambridge to identify ways in which the application of machine learning can be used to promote improved mental health through artificial intelligence (AI).
This collaboration aims to jointly explore how AI can be used to enhance SilverCloud Health’s digital mental health platform and to deliver digital CBT-based programs, making treatment more accessible.