Yann LeCun once stated that “our intelligence is what makes us human, and AI is an extension of that quality.” However, is it possible for artificial intelligence (AI) to treat mental health diseases (MHD)? MHD is a serious public health concern, and the cost of treating it is comparable to that of many other chronic physical disorders.
Starting off, given that there is more data available, AI techniques can be utilised to learn more about mental health. Deep learning (DL) techniques have recently demonstrated promising outcomes in the field of medicine, notably in the areas of diagnosis, prognosis, and treatment.
Although it has its limits, AI can improve access to integrated treatment and deal with depression. Significant flaws discovered in recent studies could portend the quick commercialization of new AI models for mental health services and research that have not yet been put to the test in the real world.
What conditions do most teenagers have?
One in five children experiences anxiety or depression, although these conditions are often not recognised until adolescence or adulthood. Screening for sadness and anxiety in kids who aren’t emotionally or linguistically developed enough to express their thoughts might be difficult. Adolescent melancholy may be avoided by recognising both the outward signs of distress and negative self-talk.
Can AI be used to treat mental illness?
AI is used by mental health professionals for a variety of goals, including enhancing understanding during therapy sessions, improving diagnosis through ongoing patient monitoring, and modifying treatment as necessary. AI refers to technological tools that can be used to diagnose and treat depression. By delivering therapy, getting feedback, and offering tailored recommendations, these tools may help in treating and managing depression.
AI for diagnosing mental disorders
AI has proven effective in a variety of fields, including medical diagnostics. Several machine learning techniques, including Boltzmann, support vector machines (SVM), and K-Nearest Neighbour (kNN), are used to recognise and diagnose diseases. AI subfields, including machine learning (ML) and computer vision, have become quite popular due to their imaging, segmentation, and prediction capabilities. Computer vision is used to recognise, separate, and categorise images in the diagnostic process, including metastatic detection, radiological image segmentation, and categorization into diagnostic categories. Schizophrenia is a serious mental illness characterised by hallucinations or delusions and a changed perspective on reality. Khan et al. proposed a deep neural network that learns the feature representation of the data to generate a diagnosis of schizophrenia using genome sequencing data as input.
AI for the treatment of mental illness
By assisting in the prediction of the response to specific drug combinations, AI can help in the development of precision pharmaceuticals. Biomarkers from neuroimaging have been used to gauge how effectively methylphenidate treats ADHD. ML models are used to distinguish between normal and malignant MRI samples. The beginning of mental diseases has been predicted using a classification of neuroanatomical characteristics.
Challenges
The efficient use of AI in medical practise is something that doctors must understand. Although more than 70% of psychiatrists surveyed globally said they planned to use AI in their everyday clinical routine (mainly for documentation), many still have doubts about the technology’s potential for improving patient care.
What programmes are offered?
Below are some instances of well-known AI-based technology that can help with depression management. The apps are intended to support rather than replace the advice of a medical or mental health expert.
WoeBot
WoeBot is an artificial conversational agent, or chatbot, that made its debut in the summer of 2017. Making mental health treatment more accessible for people suffering from depression involves simulating human conversation and offering self-help-related advice and company. Depending on your needs, the software can suggest activities and movies. Private discussions can be had with WoeBot by anyone who owns an iOS smartphone and a Facebook Messenger account.
Wysa
According to the company, Wysa is an “emotionally intelligent” AI-based bot that can “help you manage your emotions and thoughts.” Like WoeBot, Wysa is based on CBT concepts to assist users in questioning and enhancing their beliefs and behaviours. Dialectical behavioural therapy (DBT), meditative techniques, and motivational interviewing are some of the topics covered in Wysa’s presentations. Although Wysa allows for anonymous use, it gathers information when users engage in order to more precisely understand a user’s behavioural and mental health requirements and goals.
Tess
Tess is an “AI that administers highly personalised psycho-education and health-related reminders on demand” in the field of psychology. Through Facebook Messenger, SMS texting, web browsers, and mobile apps, users can engage in the programme’s text-based chatting environment.
Youper
Users of this free iOS and Android app can discuss their symptoms, behaviours, and trends with the use of AI chatbot technology. According to the startup, Youper is an “emotional health assistant” that offers individualised comments and insights based on what it learns from daily text-based chats with customers. Users can specify their needs to Youper at the beginning of a chat session. For instance, a user might require quick advice to feel less stressed or help managing chronic depression.
Conclusion
The idea of creating AI with the ideals and knowledge of human society has yet to be explored. Human knowledge will probably never be incorporated into computer programmes. However, there are some examples, such as robots working as social workers, physical therapists, and providing elderly people with cognitive help. These developments are geared towards building intelligent machines that can make deft choices. The development of artificial intelligence may have a big impact on mental healthcare.
