Machine Learning for Forecasting Anxiety: A Study on Enhancing Psychiatrist Consultation
摘要
A body's reaction to physical, mental, or emotional pressure is stress, which is the sensation of not being able to deal with these demands and circumstances. Stress is a natural response designed to help individuals cope with challenging situations by triggering a “fight or flight” reaction. However, stress can turn into a chronic condition if a person does not take steps to manage it effectively. Chronic stress, if left unchecked, can have severe repercussions on overall health. While prolonged anxiety has a negative impact on our health and can lead to side effects such as depression, insomnia, or headaches, it is crucial to identify stress early to prevent these adverse outcomes. When faced with stress, the body releases hormones like cortisol and adrenaline, which are meant to help us manage immediate challenges. However, sustained high levels of these hormones can contribute to mental health issues, including anxiety and depression. Stress can lead to increased body temperature, elevated blood pressure, and a faster heart rate, which, over time, can damage one's health. This physiological strain can result in a range of problems, from cardiovascular issues to impaired immune function. In today's fast-paced world, many people, particularly teenagers and working adults, are experiencing heightened stress levels. This rise in stress has been linked to various serious conditions, including heart attacks, depression, and even suicide. Therefore, timely identification and management of stress are crucial for preventing such severe outcomes. The goal of our project is to leverage machine learning techniques to forecast an individual's stress levels accurately. Furthermore, it assists in understanding one's stress levels better and underscores the importance of maintaining wellness. For those already diagnosed with stress, our project offers tailored medical advice to support their mental health and overall well-being.