You enter into a dispensary the receptionist welcomes you and directs you to the doctor’s office. And there you are, standing before a robot, then it begins to analyze your depression. What? That’s where we are headed to, and in a few years’ time, it won’t be anything to be surprised about – kudos to technological advancement. Nonetheless, it’s worth mentioning that technology, besides solving most human problems it’s thought to be the genesis of certain types of depression.
As in, excessive use of internet has on various occasions been linked to mental issues. For instance, in 2010, at the University of Leeds, a group of psychologists found out that there is a close relationship between too much internet use and depression.
In 2015, researchers at the University of Gothenburg reported that heavy use of technology connects with sleep problems and heightened stress in women, not to mentions how social media is thought to influence social anxiety and low-esteem in both teens and adults.
Harnessed in the way it should, technology is seen by experts as the key to practically solving the many issues that societies face. One thing that needs to be emphasized is the boundaries to which humans should allow technology to impact their lives –and if possible, better gadgets that can power those boundaries be invented. While the World Health Organization has been issuing warnings on how we are supposed to control depression triggers or be part of the menace, it’s time to be practical on just how the current and future tech can be a force for good.
Machines Detect Symptoms Accurately, Faster and Better than Humans do
How is that possible? Machine learning. Algorithms with the ability to identify patterns of human behaviors that are otherwise hidden and difficult to detect have been developed. For instance, a while ago, it was noted that often use of certain words like “very, really, and incredible” may suggest the individual is depressed. Knowledge gathered from such studies can pave way to the recognition of biomarkers -symptoms exhibited in many illnesses, and definitely offer accurate routes to diagnosis.
Experimental Proofs and Chip Improvements
At Vermont University, researchers carried out an amazing experiment which involved Instagram visual cues that show the subject is depressed, and a trained machine mastered them. Their finding seems amazing because they say the algorithm proved it could actually identify depression with up to 70 percent accuracy. On another occurrence a supercomputer was used to detect patterns in neuroimaging data sourced from brain scans, this also proved to help foresee depression at its tender age.
Talking of resources, there was a great concern in the scientific community citing that training a machine takes a lot of time. However, with the discovery of the memristors chips and others, which are said to greatly reduce machines and neural networks learning time, it will be easier to get more robots to tasks. This is also expected to improve machine data retrieval for specific uses.
Identifying Treatment Options
While facts show that it is possible to identify the various types of depression using AI, getting to establish how best to treat each unique case fast would be a great step. The use of technology can allow the experts to compile data on how patients respond to certain treatments which will help minimize trial and error.
In a study led by Uher, the team examined patterns within datasets and was able to match it with specific groups of patients. In so doing, it is possible to predict the effectiveness of a treatment. After that, Chekroud and his team did something similar in 2016 where they analyzed the way victims responded to citalopram, a new antidepressant drug. They were able to gather enough data which they used to develop a robust system and predictive model.
So far we have apps like Moodtract Diary, Mood Tracker and Moodlytics that help individuals watch their emotional patterns and the circumstances that seem to trigger their depressive moods. MoodTools and Silvercloud then come in to suggest specific activities that would manage particular forms of depression. iSee another app, helps both the patient and their counselors make decisions on whether the pill should be taken or not. These applications are beneficial in places that face barriers to economic health care.
Still relating to AI, NHS England is striving to get more people to manage their health online, on interactive platforms in a bit to personalize care.
Chatbot on 111 helpline
In a bid to cut waiting times, NHS launched a chatbot although that has since sparked different feelings to the members of the public. Ideally, the bot uses a mixture of AI, videos, and text to handle cases that are not in the real sense that urgent. Its work is to offer medical advice, and direct patients to medical services that work out-of-hours, which means the machine understands what exactly the victims needs from its collection of previous data patterns.
Well to sum it up, a keen look into artificial intelligence may offer unimaginable solutions in not only treating depression and other diseases, but it also offers greater opportunities from an entrepreneurial point of view.