AI can already diagnose depression higher than a physician and tell you which ones treatment is best

Artificial intelligence (AI) is poised to revolutionise the way in which we diagnose and treat illness. It might be particularly helpful for depression since it could make more accurate diagnoses and determine which treatments usually tend to work.

Some 20% of us may have depression not less than once in our lifetimes. Around the world,
300 million persons are currently experiencing depression, with 1.5 million Australians prone to be depressed at anybody time. Because of this, depression has been described by the World Health Organization as the one biggest contributor to in poor health health all over the world.

So how exactly could AI help?

Depression will be hard to identify

Despite its frequency, depression is difficult to diagnose. So hard, the truth is, that general practitioners accurately detect depression in lower than half of cases.

This is because there is no such thing as a one test for depression: doctors use self-reported symptoms, questionnaires and clinical observations to make a diagnosis. But symptoms of depression usually are not the identical for everybody. Some people may sleep more, others sleep less; some people lack energy and interest in activities, while others may feel sad or irritable.

For those that are accurately diagnosed with depression, there are a selection of treatment options including talk therapy, medications and lifestyle change. However, response to treatment is different for everyone, and we’ve got no solution to know ahead of time which treatments will work and which won’t.

AI trains computers to think like humans, with a selected concentrate on three human-like behaviours: learning, reasoning and self-correction (to fine-tune and improve performance over time). One branch of AI is machine learning, the goal of which is to coach computers to learn, find patterns in data and make data-informed predictions without guidance from humans.

In recent years there was a surge in research applying AI to illnesses like depression, which will be difficult to diagnose and treat.

What they’ve found to this point

Scientists have compared ChatGPT diagnoses and medical recommendations to those of real-life doctors with surprising results. When given information on fictional patients of various depression severity, sex and socioeconomic status, ChatGPT mostly beneficial talk therapy. In contrast, doctors beneficial antidepressants.

US, British and Australian guidelines recommend talk therapy as the primary treatment option ahead of medication.

This suggests ChatGPT could also be more prone to follow clinical guidelines, whereas GPs may generally tend to overprescribe antidepressants.

ChatGPT can be less influenced by sex and socioeconomic biases, while doctors are statistically more prone to prescribe antidepressants to menespecially those in blue-collar jobs.

How depression affects the brain

Depression affects specific parts of the brain. My research has shown that the areas of the brain affected by depression are extremely similar in several people. So much so, we are able to predict whether someone has depression or not with greater than 80% accuracy just by taking a look at these brain structures on MRI scans.

Other research using advanced AI models has supported this finding, suggesting brain structure could also be a helpful direction for AI-based diagnosis.

Studies using magnetic resonance imaging (MRI) data on brain function at rest can even predict depression accurately greater than 80% of the time.

However, combining functional and structural information from MRI gives the perfect accuracy, accurately predicting depression in over 93% of cases. This suggests using multiple brain imaging techniques for AI to detect depression stands out as the most viable way forward.

MRI-based AI tools are currently only used for research purposes. But as MRI scans develop into cheaper, faster and more portableit’s likely this type of technology will soon be a part of your doctor’s toolkithelping them to enhance diagnosis and enhance patient care.

The diagnostic tools you would possibly have already

While MRI-based AI applications are promising, an easier and easier approach to detecting depression could also be at hand, quite literally.

Wearable devices like smart watches are being investigated for his or her ability to detect and predict depression. Smart watches are especially helpful because they will collect a wide selection of information including heart rate, step counts, metabolic rate, sleep data and social interaction.

A recent review of all studies done to this point on using wearables to evaluate depression found depression was accurately predicted 70–89% of the time. Since they’re commonly used and worn across the clock, this research suggests wearable devices could provide unique data that may otherwise be hard to gather.

There are some drawbacksnonetheless, including the substantial cost of smart devices which could also be inaccessible to many. Others include the questioned ability of smart devices to detect biological data in people of color and the lack of diversity in study populations.

Studies have also turned to social media to detect depression. Using AI, scientists have predicted the presence and severity of depression from the language of our posts and community memberships on social media platforms. The specific words that were used predicted depression with as much as 90% success rates in each English and Arabic. Depression has also been successfully detected in its early stages from the emojis we use.

Predicting responses to treatment

Several studies have found antidepressant treatment response might be predicted with greater than 70% accuracy from electronic health records alone. This could provide doctors with more accurate evidence when prescribing medication-based treatments.

Combining data from people in trials for antidepressants, scientists have predicted whether taking medications will help specific patients go into remission from depression.

AI shows substantial promise within the diagnosis and management of depression, nonetheless recent findings require validation before they will be relied upon as diagnostic tools. Until then, MRI scans, wearables and social media could also be helpful to help doctors diagnose and treat depression.