A Non Invasive Hybrid Machine Learning Technique for Prediction of Multiple Psychological Diseases

Psychological Stress is a crucial factor in any person's health and is closely related to many illnesses, including anxiety, depression and other mental disorders. Therefore, it is crucial to keep an eye on individuals' improper behavior and provide the appropriate treatment plan. Al enabled artificial intelligence based decision taking systems and disease diagnostics have attracted a lot of interest from experts and the global research communities. There are many algorithms created and used by using data mining and machine learning based techniques that may significantly participate in the improvement of the health infrastructure and can support professionals engaged in the early detection of illnesses. Proposed system offer an additional layer that benefits patients and the healthcare services professionals through time saving during early diagnosis of critical diseases. The novel research findings presented here will aid in the identification of several mental illnesses, such as schizophrenia, obsessive-compulsive disorder, and bipolar disorder. The primary goal of the suggested approach is to develop a model which will help individuals as well as medical professionals to early detect any psychological disease and helps to start its treatment.