Mood disorders are a group of mental health conditions that involve changes in mood. These can include both highs (mania or hypomania) and lows (depression). diagnosing mood disorders can be tricky, as symptoms can vary greatly from person to person. However, new research suggests that artificial intelligence (AI) may be able to help.
A recent study found that AI was better than chance at diagnosing depression from human voice recordings. The AI was also able to identify other mood disorders, such as bipolar disorder and anxiety. This is an exciting development, as it shows that AI has the potential to improve the diagnosis of mood disorders.
What’s more, the use of AI could help to reduce the stigma surrounding mental health. By providing a more accurate diagnosis, AI could help to normalize mental health conditions and reduce the stigma that surrounds them.
When children are ill, the mother can often tell something is wrong just by looking at them. Then, she leaps into action right away. After recognizing the problem, the mother employs a combination of home treatments, diet, activity, and rest to nurse her children back to health.
Timely care and maternal attention resolve the health issue long before it becomes a sickness. However, the children are unaware that they are ill in most situations.
Wouldn’t it be fantastic if we could detect and treat depression symptoms in adults in their early stages, similar to how mothers discover health issues in their children?
Mental health has become one of the world’s most pressing issues. The CDC in the United States is concerned that one in every two Americans could get depression or mood disorder due to the pandemic.
Unfortunately, according to medical estimates, around two-thirds of all mood disorder and depression cases go misdiagnosed.
According to recent advances in artificial intelligence (AI), providers can now diagnose depression simply by listening to someone utter a few lines, according to recent advances in artificial intelligence (AI). But, how you express things is more important than the wording you choose.
Let’s look at how AI can help identify mood disorders, its benefits to patients and therapists, and some significant trends emerging in this field.
Diagnosing Depression
Scientists have long thought that one could tell whether a person was depressed based on their voice. However, in a 2012 study, the research team found that this may not be the case.
The research project, sponsored by a small-business innovation research grant from the US National Institutes of Health, purportedly found vocal-acoustic markers correlated with the severity of specific depression symptoms.
Dr. James Mundt is a senior research scientist at CPC who led the 2007 and 2012 studies. As people recover from depression, they speak faster and with shorter pauses–or in a lifeless, metallic quality if they do not.
All speech requires complex control of the nervous system, and the underlying pathways in the brain can be impacted by psychiatric disorders such as depression. For example, the capacity to speak is associated with thought, which is associated with depression.
In the meantime, a depression screening tool the company is working on detects the severity of depressive episodes. Patients speak into a microphone to record a voice sample which the company’s algorithms then analyze to measure the levels of anxiety or depression.
Our team combined deep learning and cutting-edge transfer learning techniques to create voice models that detect acoustic and word-based patterns. As a result, they are the first voice models to not rely on predetermined features.
And since voice is an original measure of well-being, through speech, someone’s voice conveys their internal state- not only through words and ideas but also through tone, rhythm, and emotion.
How This Changes Everything for Health Professionals
For health care providers, it is a tool that enhances the clinician’s capacities. The following are some examples of how this changes things for health practitioners.
- Clinicians are using AI to actively listen to patients to diagnose or recognize speech patterns, providing there are no privacy problems. It is comparable to how natural language processing (NLP) now assists health coders in transcribing patient notes to determine a medical diagnosis.
- Clinicians encourage patients to converse with AI to track and monitor their progress. A physician can tell if a patient has stopped taking medicine, has relapsed mood disorder, and vomiting.
What Benefits Does AI Voice Analysis Bring in?
- Efficiency
By examining behavioral signals, AI Voice Analysis algorithms have already been shown to successfully recognize indications of depression, PTSD, and other illnesses.
Other research has found that algorithms are 100 percent accurate at predicting who among at-risk youth is likely to develop psychosis and make more accurate assumptions than physicians in distinguishing between genuine and fraudulent suicide notes.
They also assist patients experiencing mental distress: a randomized controlled experiment conducted by AI chatbot Woebot researchers.
- Privacy And Ease To Open Up
Artificial intelligence therapists can feel less intimidating and encourage people to open up about topics they otherwise would not feel comfortable with because they can be shy.
Approximately one in four people lie to their doctors. The most insane topics are smoking, drinking habits, and sexual activity. For many, it’s easier to admit the truth to a robot because the robot will not judge.
- Support for Therapists
AI could help professionals make the most of the time they have with their patients.
This is because AI can track and analyze large amounts of data faster and more efficiently than humans. As a result, algorithms aid in the development of more precise diagnoses.
They can also detect early warning indications of trouble by monitoring the patient’s mood and behavior and alerting professionals so that treatment plans can be rapidly adjusted. Suicidal individuals who require regular check-ins may find this life-saving.
- Accessibility
The use of AI voice analysis for mood disorders eliminates specific barriers to treatment, including shortages of providers across the board and not enough of them in rural and remote areas.
It is essential as more than 100 million people in the US live in what are known as Health Care Professional Shortage Areas. Digital chatbots that aren’t location-specific can see you whenever you need and spend as much time with you as you require.