Leveraging AI to Improve Mental Health Diagnosis and Treatment

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Researchers and clinicians have found out that artificial intelligence (AI) can enhance the field of mental healthcare to a great extent. According to a growing department of evidence, AI is capable of developing therapies, diagnosing conditions, and establishing customizable treatments and approaches.

Since the onset of coronavirus, a larger segment of the population has been seeking help for anxiety and depression. It is quite unfortunate that suicide is now one of the leading causes of death among 14-to-30-year olds. This is creating pressure on the already-stretched therapeutic and medical services, which have become hard to access. Could smart machine learning technologies be a solution? Could they cure patients without medication?

Below are some of the ways in which artificial intelligence is being utilized to modify lives and improve patient outcomes for a wide range of mental conditions.

1. AI Therapists

Would you prefer talking to some robot about your deepest and most intimate emotions?

Chatbots have been offering advice to and communicating with patients during a treatment. They can help you cope with symptoms and look out for a specific keyword that can trigger a referral or direct contact with a human doctor.

One popular AI therapist is Woebot. It can adapt to a patient’s personality and talk him/her through different therapies and exercises. Another therapist, Tess, provides 24/7 emotional support and can allow patients to cope with panic and anxiety attacks.

2. Personalized Treatments

A leading website stated that medical professionals can leverage AI to create a plethora of personalized treatments. AI can monitor symptoms and reactions to a particular treatment. The data collected can be further utilized to tailor individual treatment plans. One research conducted at the California University concreated om creating personalized treatment for kids experiencing schizophrenia based on digital vision of brain images. A significant component of this research is explainable AI. Doctors should understand the algorithms.

3. Wearables

Instead of waiting for a patient to interact through an app, many AI mental health solutions operate as wearables. They can interpret bodily signals with sensors and provide help whenever required.

One major example of AI wearable is Biobeat. It gathers information on physical activities, sleeping patterns, and discrepancies in heart rate that are then used to analyze a user’s cognitive state and mood. The information is compared with anonymized and aggregated data from other patients to offer alerts when intervention is needed. Users must then have to change their behavior or get assistance from medical services.

4. Patient Compliance

The biggest challenge of curing mental health issues is making sure a patient adheres to the prescribed treatment such as medications or therapy sessions.

A reputed website suggested that AI can predict if a patient is likely to non-comply and issues reminders or notifies a healthcare expert to arrange manual interventions. This is done through chatbots like those mentioned in the first pointer or through emails, SMS, automated phone calls, etc.

Algorithms can successfully identify behavioral patterns and occurrences in a patient’s life that can trigger non-compliance. This information is then passed on to healthcare experts who can collaborate with the patient to develop strategies of eliminating those obstacles.

5. Patient Outcome

AI can also analyze medical and behavioral information through recordings collected from telephonic and one-to-one interventions. Machine learning can flag warning signs of various mental health problems before they can worsen.

According to various research projects, artificial intelligence and machine learning can predict and categorize mental health problems such as depression, schizophrenia, suicidal thoughts, etc. with excellent accuracy. Data sources that were studied included brain images, electronic medical records, social media info, and video monitoring solutions. Researchers can also depend on AI to help individuals who may not have mental health problems right now but may develop symptoms in the future.

AI can also predict cases if the patients will respond well to cognitive behavioral therapy (CBT) and therefore do not need medication.

As evident from the above discussion, artificial intelligence has the capacity to contribute to mental healthcare.  However, make progress carefully, and evaluate methods and models before using them in real-life situations. Anyway, I am hopeful that artificial intelligence (AI) can treat difficult conditions and eliminate the disastrous impact mental health issues have on human beings.