Artificial Intelligence (AI) tools are extensively used across multiple industries, including healthcare, medicine, and research. Medical researchers have given a mark of credence to the uses and applications of AI technologies. As an important advancement, researchers have developed an algorithm that can detect signs of depression in children’s speech.
The algorithm uses machine learning technologies to analyse speech patterns in kids. Several medical conditions related to children often go unnoticed due to negligence and contempt. Further, child depression and anxiety is one such condition that needs more attention from the medical fraternity. Therefore, the research focuses on spotting speech patterns that could help in diagnosing depression in children. The Journal of Biomedical and Health Informatics published the findings of the research.
Getting Cues from Speech Patterns
Disorders related to child depression, anxiety, and stress are termed as “internalizing disorders”. It is appalling to note that one in every five children suffers from depression and anxiety. However, children below the age of eight cannot articulate or explain their emotional distress. Hence, it’s important for adults to get cues related to children’s mental health through their actions and speech. This shall help in quick diagnosis of depression and anxiety in children. Getting medical appointments with doctors and psychologists can be a lengthy and cumbersome process. In this scenario, machine learning tools can help parents in analysing the mental health of their children.
Need for Improved Rate of Diagnosis
Clinical psychologists believe that most children under the age of eight miss out on important treatment. This is because their depression and anxiety go undiagnosed during that phase of life. It is expected that the new algorithm would largely help in improving the mental health of children.