Mental Health Experts And Machine Learning Go Hand In Hand
Depression is the most prevalent mental health illness in the world, with over 3.8 per cent of the population suffering from it. Though, growing awareness among people is a significant reason for the change in the world's view of mental health. There is still a lot to be done. The stigma surrounding mental health prevents individuals suffering from serious mental health conditions from seeking medical intervention and is also a reason for the many premature deaths of the affected individuals.
Today, psychological health and well-being are beginning to receive a well-deserved priority in our lives. This has encouraged more and more individuals to seek assistance from medical professionals to help manage their mental health. While the traditional route is to start with therapy and medication, the recent developments in technology are opening the doors to enhancing the treatments and showing the potential to predetermine the onset of conditions affecting an individual's mental health.
One such vital development uses Machine Learning, a form of Artificial Intelligence(AI), to assist mental health practitioners in determining an appropriate course of action to help their patients. Neuroscientists and doctors are working with deep learning to develop treatment strategies and determine biomarkers for specific illnesses to proactively help identify patients at risk of developing the disease in future.
The ongoing research in the area looks to develop the means to help patients manage difficult conditions such as dementia, schizophrenia, depression etc., using digital elements such as wearable devices and smartphones. These devices will aid individuals in taking better charge of their mental well-being, will work to minimise the stigma surrounding the topic and also assist medical professionals in refining their diagnoses.
A prime example is the collaborative research project conducted by MIT's Professor Rosalin Picard, the Principal Investigator at the Jameel Clinic for Machine Learning in Health, and Massachusetts General Hospital's Paola Pedrelli, Associate Director of the Depression Clinical and Research Program. The duo is working to develop deep learning algorithms to help analyse and observe changes in symptoms in patients suffering from a significant form of depressive disorder.
Varying factors can affect an individual's mental health. And while their near and dear ones try their best to understand and help them, they might miss the subtle changes in the individual's behaviour which could indicate the onset of a mental health condition or help them manage an existing one.
Digital devices and AI can help effectively diagnose and monitor mental health issues by handling large data inputs like heart rate, activity, socialisation patterns, stress patterns etc., used for determining commonalities and offering relevant results. These results can assist in the detection of triggers, help mental health experts determine a personalised treatment plan and even offer gentle suggestions to improve the individual's mood and overall well-being. Since the software or application is not programmed to provide specific outputs, it uses real-time data to refine its analysis and improve as it functions, which is another advantage machine learning affords us.
The emergence of this technologically reinforced support for healthcare practitioners takes us one step closer to creating a safe and nurturing environment for individuals who suffer from mental health conditions. I believe this is a true example of how technology can help make the world a better place.
