Globally, there is growing awareness and concern about mental health heightened by the COVID-19 pandemic. India accounts for 15% of the world’s mental illness population, and the country has a significant treatment gap that healthcare professionals are attempting to close. While there are various reasons for this, the most common is social stigma. This poses a crucial question: how will we ever meet this growing need, and how might technology assist?
Artificial intelligence (AI) strengthens critical areas, such as healthcare and education, through things that can help and offer new beneficial opportunities. AI for mental health could be the next big thing. Healthcare AI can bring positive change in a sector that has long been primed for innovation due to the rapid pace of technological advancement.
The role of AI in improving mental health
Many people believe that mental healthcare is a human-only profession requiring emotional intelligence, unlike medical specialties such as radiology or pathology, where AI can outperform doctors. Most mental health experts are skeptical of using AI, machine learning (ML), or natural language processing (NLP) to provide empathic care. Researchers believe that while robots can augment traditional evaluation approaches, they are not prepared to replace mental healthcare experts. According to a Cambridge study, robots are more advantageous than parent- or child-reported tests for identifying children with mental health problems.
Examples of how artificial intelligence is transforming mental healthcare
Businesses worldwide are implementing AI to improve customer service and create new opportunities. In a sector like healthcare, AI is the right technology to handle the increasing number of data, particularly in a country like India, which can analyze massive amounts of unstructured data. Healthcare practitioners are using AI to speed up patient recovery, improve the accuracy of medical analysis for individualized care, and prevent illnesses via timely interventions.
Monitoring of patients for early detection
Since the pandemic, there has been an increase in public awareness of the importance of preventive healthcare, which has resulted in the popularization of the internet of medical things. Passively gathered physiological and behavioral data has aided in the diagnosis of many mental health problems. Direct physiological data monitoring has been challenging until recently because of the size, cost, and mass of such equipment (e.g., heart rate, sleep quality, skin conductance). However, the proliferation of wearable devices such as wristbands, smartwatches, and fitness trackers, as well as the wide usage of smartphones, has made it easier to collect physiologically important data. As a result, new technologies to promote mental health are being developed rapidly. The ability to detect severe illnesses earlier has increased the possibility of saving lives.
Conversational artificial intelligence
Conversational AI enables clinicians to have one-on-one talks with their patients. Conversational healthcare is increasingly becoming recognized as a means of providing the finest treatment possible based on the patient’s specific requirements. According to a Market Research Future poll, more than 52% of individuals use healthcare chatbots to get information, while 36% of doctors allow to use them to treat patients. Conversational AI-powered medical chatbots help minimize hospital visits, unnecessary treatments and procedures, hospital admissions and readmissions. Wysa, for example, is an AI-based chatbot that can read user inputs after being trained with 100 million conversations.
Observing the patient speech and behavior
Healthcare organizations have already begun to use AI technology to deliver precise and up-to-date information to patients without needing them to visit hospitals. Few people know that a person’s voice might change slightly every few milliseconds due to changes in their body and medical issues. This vast amount of data can be used to establish the voice features that correspond to certain sickness symptoms or health changes. Using data collected from thousands of people suffering from medical disorders such as anxiety and depression, we can train ML models to teach AI engines to recognize vocal patterns typical of these people.
Recognizing the need for mental health care
Unexpected search results are seldom pleasant; they can even be dangerous and upsetting sometimes. By using the Safe Search option, users can exclude direct results. However, sometimes that is exactly what a person is looking for. Google’s AI-powered Multitask Unified Model, or MUM, can automatically and more precisely identify a broader range of personal crisis requests, states Google in a blog. MUM can more precisely detect the motives behind a person’s searches and pick when to give them credible and relevant information when they are in need.
AI can help but not replace human therapists. It provides help around the clock and can serve as an early warning system. Some apps, for example, identify suicidal thoughts during counsellor discussions and initiate a 911 call. Individuals living in rural areas with limited access to mental healthcare or those unable to afford frequent therapy sessions may find AI-augmented services to be a lifeline.
In India, where numerous unorganized sectors, communities, languages, and dialects exist, digitization procedures are sometimes insufficient and unclear, and there is no central database for health records. As a result, data for AI organizations may not adequately represent a significant section of the population. However, AI-driven models can collect and arrange data to create a technology-driven ecosystem that will empower mental healthcare specialists. This can help healthcare personnel better understand patient needs by utilizing AI and ML in care delivery and management, allowing them to provide more guidance and aid in maintaining excellent mental health.
Read More: Artificial Intelligence In Healthcare