{"id":9006,"date":"2019-05-30T14:04:20","date_gmt":"2019-05-30T18:04:20","guid":{"rendered":"https:\/\/blog.brainstation.io\/?p=9006"},"modified":"2020-05-07T13:00:03","modified_gmt":"2020-05-07T17:00:03","slug":"how-ai-can-help-diagnose-and-treat-mental-illness","status":"publish","type":"post","link":"https:\/\/brainstation.io\/blog\/how-ai-can-help-diagnose-and-treat-mental-illness","title":{"rendered":"How AI Can Help Diagnose and Treat Mental Illness"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Even though mental illness begins in the brain, diagnosing it through brain imaging has typically proved elusive for clinicians.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">There are a lot of reasons why. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Different psychiatric conditions like bipolar disorder or anxiety share similar symptoms, like irritability. Even conditions like depression can have a myriad of symptoms that can change depending on the person, <\/span><a href=\"https:\/\/www.psychologytoday.com\/ca\/blog\/think-act-be\/201605\/using-brain-scans-diagnose-mental-disorders\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">notes Seth Gillihan<\/span><\/a><span style=\"font-weight: 400;\">, a Clinical Assistant Professor of Psychology at the University of Pennsylvania, in Psychology Today.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">And while Researchers are getting closer to pinpointing certain areas of the brain impacted by different illnesses \u2014 such as the amygdala, an area that processes fear, in patients with post-traumatic stress disorder \u2014 there\u2019s also a lot of overlap and a lot of questions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">But in the years ahead, experts say some of those questions could be answered through artificial intelligence.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cUnfortunately, no one knows how different parts of the brain interact,\u201d says <\/span><a href=\"https:\/\/www.ualberta.ca\/science\/about-us\/contact-us\/faculty-directory\/russ-greiner\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">Russ Greiner<\/span><\/a><span style=\"font-weight: 400;\">, Professor in the <\/span><span style=\"font-weight: 400;\">Department of Computing Science<\/span><span style=\"font-weight: 400;\"> at the University of Alberta. \u201cWhat we do have are data sets.\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Data that could one day contain information on hundreds or thousands of previous patients, and could be capable of building classification systems to apply to new patients in need of a diagnosis, he says.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">While Greiner says the technology isn\u2019t still in the works, his research is already pointing at the widespread clinical possibilities of AI in the diagnosis of mental illness.<\/span><\/p>\n<h2><b>Interpreting Brain Scans Through AI<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Along with a team of UAlberta Researchers, Greiner conducted a 2019 study using machine learning to identify schizophrenia in brain scans.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The team developed a form of AI which trained on \u2014 and learned from \u2014 numerous brain scans of previous patients diagnosed with the complex mental disorder, which is often marked by abnormal behavior, hearing voices, and an overall inability to understand what\u2019s real and what\u2019s not.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The technology \u2014 dubbed EMPaSchiz, or the Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction \u2014 looks at thousands of features in a patients\u2019 brain scan to make a prediction. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">The team\u2019s research showed EMPaSchiz could identify schizophrenia accurately 87 percent of the time for new scans. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cOne issue with psychiatric diagnosis is that it is subjective,\u201d says Greiner, who\u2019s also the Principal Investigator of the Alberta Machine Intelligence Unit. \u201cOne thing I like to do is have measures not based on what a psychiatrist does, but on the actual patient characteristics.&#8221;<\/span><\/p>\n<p><span style=\"font-weight: 400;\">While widespread practical application is a long way off, he says the goal is developing targeted treatments for each patient, instead of cycling people through different options that may or may not work \u2014 a tiring and potentially-dangerous process that can leave patients in limbo for months, or even years.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Researchers hope \u201cto make patients suffer less, and for less time,\u201d he says.<\/span><\/p>\n<h2><b>Apps and Wearables Entering Mental Health Sphere<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Beyond diagnosing brain scans, Greiner also predicts AI will enter the mental health sphere in other ways in the years ahead.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">From Alexa to Siri, various apps and their parent companies are already starting to dabble in the healthcare space, for instance. \u201cGiven the Fitbits and smartphones, I think there&#8217;s more and more of these other options for psychiatric diseases,\u201d Greiner adds.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">It raises big questions: What if our always-on technology could catch issues with our mental state, by sensing our words and actions? What if they checked in the way a helpful colleague or family member would do?<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cYou could have tools which monitor you and give advice,\u201d Greiner says. \u201cThink of what your mother would do: \u2018Fred, I think you seem out of sorts.&#8221; People&#8217;s mothers may not be doing it, but their cell phones might.\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">BioBeats, for instance, is one UK-based app founded in 2013, which identify stress patterns using sensors in smartphones and wearables, <\/span><a href=\"https:\/\/www.forbes.com\/sites\/lucysherriff\/2019\/03\/25\/how-one-company-is-using-ai-to-address-mental-health\/#1a5d7d5d1319\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-weight: 400;\">Forbes reports<\/span><\/a><span style=\"font-weight: 400;\">. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">By coupling the sensors with behind-the-scenes machine learning, the technology allows users to understand how their body is responding to stress and potentially take preventative action for the sake of their mental health.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Greiner says AI could potentially even help prevent addiction relapses or suicide, by flagging unusual behavior or dangerous locations to a person or their loved ones \u2014 be it an alert reminding someone they\u2019re in a neighbourhood where they typically buy drugs, or one offering a crisis helpline if an app determined their search history pointed to suicidal thoughts.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cEven if these people withdraw from human contact, they still have their cell phones,\u201d Greiner says. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cA friend could be aware of these things. Why couldn&#8217;t the artificial intelligence tool that&#8217;s with you?&#8221;<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI (and machine learning) may be opening up new widespread clinical possibilities.<\/p>\n","protected":false},"author":7,"featured_media":9009,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[859],"tags":[494,810,911,912],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v18.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How AI Can Help Diagnose and Treat Mental Illness | BrainStation\u00ae Blog<\/title>\n<meta name=\"description\" content=\"Diagnosing and treaining mental illness has always been challenging, but AI and machine learning may be creating new widespread clinical possibilities.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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