In the midst of the mental health crisis, researchers have achieved the incredible feat of creating AI for mental health which might be a sign of good gesture for future generations
A report by the World Health Organisation (WHO) estimates that 38 million Indians suffer from anxiety while 56 million people have depression. In addition, the number of psychiatrists and psychologists in India is drastically low in comparison to the number of people who are suffering from mental illness.
Another survey done by the National Mental Health Survey reveals that nearly 10.8 percent of Indian adults need active intervention for one or more mental health issues, out of which 0.8 percent suffer from severe mental disorders. To deal with this ongoing mental health crisis, companies are testing ways in which Artificial Intelligence (AI) can help treat mental illnesses with the help of an AI-powered automated solution for mental assessment.
DigiconAsia spoke to Kalyan Ganjam, Senior Technical Architect - Prolifics to find out how medical practitioners can take the help of AI to treat patients with mental health issues -
What role can AI play in helping treat mental disorders and illnesses?
The onset of Covid- 19, in the absence of easy access to physical clinics had led to a dramatic increase in the use of technology-based healthcare platforms. This was largely restricted to consultation but has been beneficial in the mental health field without losing its effectiveness. AI can be used to stimulate digital conversations with especially the youth in crisis to help reach a wider population at a faster rate. A thorough understanding of a patient's requirements and progress may be achieved through the application of AI in mental health care, which can then be used to prescribe a highly tailored and successful course of therapy.
Apart from this, AI tools are available 24/7 at no cost and reduce the stigma around accessing treatment. These tools can either be used as stand-alone treatment agents or as a supplement to traditional therapy. Due to the anonymity of an AI algorithm, people might find it easier to talk and open up to a bot.
How can it help a medical practitioner in assessing mental health better?
With the help of Artificial Intelligence, it has become easier for a medical practitioner to diagnose mental health issues better. Deep learning (DL) and machine learning (ML) technologies offer higher precision in mental health issue diagnosis and patient outcome prediction. The application of artificial intelligence in mental health can be a great aid for professionals as algorithms are capable of accurately detecting a variety of mental diseases with higher accuracy, depending on the choice of an AI approach and the caliber of training data.
How is it going to be different from a traditional counselling setup?
AI-powered tools can detect problems before humans can. Studying repeated patterns through a large data set avoids the possibility of a mental health issue escalating. Chatbots are available everywhere at all times at a very low cost. Infact some people might even be more comfortable in sharing their problems on chat versus a human being. When deemed necessary, doctors can be alerted to intervene at the right time to combine human expertise.
What are the future prospects of using AI in the field of mental health?
More AI therapists and other mental health products powered by AI's prediction and detection skills are probably on the horizon. The initial outcomes of using AI in mental health are encouraging, but the future of long-term effectiveness has not yet been proven. Although it depends on a number of things, AI will undoubtedly become a solution to the delivery of mental healthcare if the industry can get past several significant roadblocks. It can significantly contribute to the cure of the mental health crisis, and with the creation of safe, dependable, and impartial AI technologies, the way mental health is handled will change.
What are some of the latest trends with AI in mental health?
There are already techniques that can accurately diagnose mental health issues and devise a treatment route. Other trends include Natural language processing NLP for speech recognition and text analysis is used to create and comprehend clinical documentation as well as to simulate human interactions with chatbot computer programmes. Understanding non-verbal indicators including facial expression, gestures, eye contact, and voice tensing using computer vision for image analysis.
Several mental health clinics are currently experimenting with automated ways to monitor the quality of therapy sessions. Tech firms are working on tools that can help to better understand the conversation between therapists and clients. Such tools can help ensure high standards of service and can prove to be a game-changer.
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