QMH (Quantifying Mental Health) Key Technologies

Vollständiger Abstract

Worum geht es in dieser Arbeit?

In order to understand the chaotic nature of mental health, a forensic simulation of the mental health system is under development. This paper discusses the requirements and key technologies based on Ontological Engineering. Ontological engineering is expected to provide a foundation of so-called Content-Directed Artificial Intelligence which relies on the development of an _integrated World Knowledge DataBase _(_WKDB)_ necessary for the understanding of mental health. Artifical Intelligence is based on the design of it's creator/s and as such unknowingly “bias creep” can easily be imbedded into the design of its WKDB[1]. Mental health techniques are required in order to develop a mitigation plan for the alleviation fo pain which is of both mental as well as physical. This paper address the requirements for the mitigation of mental pain. Specifically anxiety and depression are the most common problems, with around 1 in 10 people affected at any one time. What is the cause of mental health problems problems and what is it's affect? Anxiety and depression can be severe and long-lasting and have a big impact on people's ability to get on with life. Predictions of beliefs and thoughts (good and bad) are brain outputs due to the measured vision, hearing inputs, and autonomic activation of one's residual WKDB. Currently our QMH Forensic Simulator yields potential target pharmaceutical parameters which could be used in the design of experimental medication for mental health patients. Additional medical producals could then be designed for use in future mental health clinical trials.