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Can AI Cure Mental Health Disorders?




How can AI help with Mental health?


In today’s world, the need for mental health resources is urgent. Globally, in addition to great need for mental health services, there is simultaneously a shortage of mental health providers. As we know, AI refers to the concept of computers solving problems on their own. What better way to help us solve this problem and create more resources than with AI? In fact, artificial intelligence is making advancements in many exciting areas of mental health.



Why is Mental Health Important?


According to recent data from the WHO, nearly one billion people suffer from mental illness. Mental health issues are increasing worldwide. In the past ten years, there has been a 13% increase in mental health illnesses and substance use disorders, primarily due to demographic shifts (2017). In the present day, 1 in 5 people live with a disability due to mental health issues. The recent impact has been mainly due to the use of social media and the COVID-19 pandemic. Overall health and well being is heavily influenced by mental health. Mental health status is fluid over the course of life. How we feel also affects how we interact with others, treat ourselves, make healthful decisions, and handle stress. Mental health status also has implications for physical health. For example, depression can increase risk of diabetes, immune system function, stroke, and heart disease



AI Diagnosis


Could there one day be an AI psychiatrist? The NIH estimates that as many as two thirds of those suffering from depression go undiagnosed. A new voice processing technology powered by AI may offer a solution. In fact, recent advancements in technology show that AI is able to detect depression twice as reliably as humans can. AI extracts data from a sample and subsequently evaluates a variety of metrics within the sample. For example, the technology can detect signs of depression by analyzing vocal biomarker data, such as pitch or rhythm of speech, from an audio sample. Currently, we still need a human to diagnose depression and other mental illnesses. However, there is huge potential for AI to shape behavioral and mental health care.



Data Science Can Provide Personalized Treatment


Each individual has their own unique needs, and different types of mental health conditions as well as individual personality traits will respond best to a particular type of therapy, therapist, or medication. For example, currently a patient may need to trial several different types of medication before finding the most effective depression medication for them. Machine learning can help make advancements by monitoring trends and collecting data to streamline this process. For example, research using brain imaging and machine learning was able to find correlations between an individual’s neural responses to emotional conflict and likelihood of benefit from an SSRI. Instead of using trial and error, why not use artificial intelligence and mental health algorithms to find the right treatment more quickly?



Expanded Access Thanks to AI


Some additional benefits to using AI include improved access to resources conveniently and at lower cost than traditional therapy. For example, an emotionally intelligent AI chatbot, called WoeBot, uses mental health algorithms to manage distressing thoughts and feelings. This chatbot monitors moods and creates a positive, therapeutic experience for its users. For those experiencing anxiety due to social anxiety or stigma, this tool is a great resource, offering additional support as well as privacy and anonymity. Additionally, these tools offer additional, around-the-clock support in between therapist sessions, giving patients life tools to manage their symptoms.



Optimizing Mental Health with AI


AI data collection can offer insights for therapy sessions. For example, making use of wearable devices such as a FitBit to monitor quality of sleep and other metrics. For example, the therapist receives objective data and can spot trends to focus on, such as sleep hygiene or emotional wellbeing. The clinician is able to make good choices about areas of improvement for patients based on helpful, objective data.



Winning Combination: Human Expertise and AI Data Analysis


Using AI to analyze vast amounts of big data and spot trends will help us to make connections and advancements more quickly than humans alone could do. For example, AI can spot trends within complex data such as family history, effective past treatments, patient behavior, and other factors to provide a more precise diagnosis and help both patient and clinician to achieve the best outcome. While these tasks are best synthesized by AI, human interactions involving empathy will still be best left to humans. The winning combination of human expertise, skills, and abilities in addition to artificial intelligence tools, means that the future of mental health is full of possibilities.



AI use in mental healthcare


While several research and development projects are in progress, AI has not been widely integrated into clinical practice — although some AI programs are being used or explored for use in mental health services. In diagnosis and prevention, AI is mainly used to determine the presence of mental illness or assess risk (e.g., by analyzing words in messages or detecting changes in behaviour), and to direct users to appropriate support. In treatment, AI usually takes the form of a conversational agent that delivers psychological treatment (e.g., cognitive behavioural therapy).

Future research could focus on the suitability of AI for mental health interventions (i.e., whether they should be used as a screening tool, a replacement for human therapists, or an adjunct intervention) and on including individuals with lived experience (e.g., asking them why they use AI and for what purpose).


The Future of Mental Health with AI


In conclusion, combining both healthcare professionals’ expertise with AI tools has exciting future implications for mental health. Mental health challenges currently affect 1 in 8 people globally, and thus improving access to resources and advancements in treatment are vital to maintaining health, both mentally and physically. AI can fill a gap in the area of mental health and increase access conveniently, cost effectively, and efficiently.



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