Around one in five children suffer from anxiety and depression, collectively known as "internalizing disorders." But because children under the age of eight can't reliably articulate their emotional suffering, adults need to be able to infer their mental state, and recognise potential mental health problems. Waiting lists for appointments with psychologists, insurance issues, and failure to recognise the symptoms by parents all contribute to children missing out on vital treatment. "We need quick, objective tests to catch kids when they are suffering," says Ellen McGinnis, a clinical psychologist at the University of Vermont Medical Center's Vermont Center for Children, Youth and Families and lead author of the study. "The majority of kids under eight are undiagnosed."
A machine learning algorithm can detect signs of anxiety and depression in the speech patterns of young children, potentially providing a fast and easy way of diagnosing conditions that are difficult to spot and often overlooked in young people, according to new research published in the Journal of Biomedical and Health Informatics. Around one in five children suffer from anxiety and depression, collectively known as "internalizing disorders." But because children under the age of eight can't reliably articulate their emotional suffering, adults need to be able to infer their mental state, and recognise potential mental health problems. Waiting lists for appointments with psychologists, insurance issues, and failure to recognise the symptoms by parents all contribute to children missing out on vital treatment. "We need quick, objective tests to catch kids when they are suffering," says Ellen McGinnis, a clinical psychologist at the University of Vermont Medical Center's Vermont Center for Children, Youth and Families and lead author of the study.
The study conducted by researchers at the University of Vermont in the USA suggests a machine learning algorithm might provide a fast and easy way of diagnosing anxiety and depression – conditions that are difficult to spot and often overlooked in young people. "We need quick, objective tests to catch kids when they are suffering," said study lead author Ellen McGinnis, who is a clinical psychologist at the university's Medical Centre's Vermont Centre for Children, Youth and Families. "The majority of kids under eight are undiagnosed," she added. Early diagnosis of these conditions is critical as children respond well to treatment while their brains are still developing, according to the researchers, but if they are left untreated they are at greater risk of substance abuse and suicide later in life. Standard diagnosis involves a 60-90-minute semi-structured interview with a trained clinician and their primary caregiver.
Welcome to Small Humans, an ongoing series at Mashable that looks at how to take care of – and deal with – the kids in your life. Because Dr. Spock is nice and all, but it's 2019 and we have the entire internet to contend with. When Ellen McGinnis started her career as a psychologist several years ago, she realized just how hard it can be to spot anxiety and depression in young children. Though they have complex inner lives and sometimes develop mental health disorders, preschoolers don't always show the traditional symptoms you'd expect to see in older children or adults, nor do they always have the words to express their feelings. McGinnis, now a clinical psychologist at the University of Vermont Medical Center's Vermont Center for Children, Youth and Families, also worked with parents experiencing their own mental illness, and they found it particularly difficult to gauge their children's emotions and moods.
Scientists in the US say they have created machine learning algorithms that can identify depressed people by scanning for "clues" in Instagram photos. The researchers from the University of Vermont and Harvard University claim their algorithm's detection rate is 70%, adding that it is "more reliable than the 42% success rate of general-practice doctors diagnosing depression in person". "This points toward a new method for early screening of depression and other emerging mental illnesses," says Chris Danforth, of the University of Vermont. The research was done in two stages: the first was about identifying the clues on Instagram photos that suggests the user might be depressed, while the second stage involved teaching the computer to detect those people using machine learning algorithms. The scientists asked for access to the Instagram feed and mental health history of 166 participants, half of whom were reported to have been clinically depressed in the last three years.
WASHINGTON – Your next doctor could very well be a bot. And bots, or automated programs, are likely to play a key role in finding cures for some of the most difficult-to-treat diseases and conditions. Artificial intelligence is rapidly moving into health care, led by some of the biggest technology companies and emerging startups using it to diagnose and respond to a raft of conditions. California researchers detected cardiac arrhythmia with 97 percent accuracy on wearers of an Apple Watch with the AI-based Cariogram application, opening up early treatment options to avert strokes. Scientists from Harvard and the University of Vermont developed a machine learning tool -- a type of AI that enables computers to learn without being explicitly programmed -- to better identify depression by studying Instagram posts, suggesting "new avenues for early screening and detection of mental illness."
Researchers from Harvard and the University of Vermont have found a way to use Instagram to detect depression. Using machine learning tools, they developed a model that can predict whether a person is clinically depressed with surprising accuracy, just by looking at their Instagram photos. It's important to note right away that this model is just the beginning. The researchers themselves only go so far as to say that "these findings suggest new avenues for early screening and detection of mental illness," and "the findings reported here should not be taken as enduring facts." That said, their results are impressive.
A new AI programme has been developed to attempt to accurately detect signs of depression using Instagram photos. The study, carried out by researchers from Harvard University and the University of Vermont, used machine learning tools to identify markers of depression. It was found that the programme was 70 per cent accurate in detecting signs of depression, which was better than previous studies looking at the success rate of GPs diagnosing patients – normally around 42 per cent accurate. Other factors were also taken into consideration such as how often users posted, as it is said depression can often be linked to reduced social activity, how many people were in the photo and the likes and comments received on each image. The study, published on Arxiv, found photos posted by individuals diagnosed with clinical depression were more likely to be bluer, grayer and darker.
A new artificial intelligence program can pick up on the early signs of depression before humans (and even humans who are general practitioners) can -- and just by using Instagram. A team of researchers from Harvard and the University of Vermont recently developed a machine learning program that correctly identified which Instagram users were clinically depressed with 70 percent accuracy. In a study published on Aug. 10 from Andrew G. Reece and Christopher M. Danforth, the group applied the machine learning platform to 166 Instagram profiles containing 43,950 photos. The system uses markers to detect if Instagramers are depressed, analyzing aspects like color, metadata, and face detection. "Using only photographic details, such as color and brightness," the study says, "our statistical model was able to predict which study participants suffered from depression, and performed better than the rate at which unassisted general practitioners typically perform during in-person patient assessment."
How do you tell if someone's depressed? Sometimes you might not know that you're depressed, but it seems that researchers from Harvard and the University of Vermont have developed an AI that will be able to tell if someone's depressed just by looking at their Instagram photos. By using "color analysis, metadata components, and algorithmic face detection", the A was able to correctly identify people who have been diagnosed with depression 70% of the time. It was also able to pick out depression based on the filters that were used. Apparently people who feel depressed tend to lean more towards bluer, grayer, and darker tones, with filters like Inkwell and Crema being used the most.