Artificial intelligence powered diagnosis model for anaesthesia drug injection

In recent years how the engineer plays a vital role in the biomedical field for medical diagnosis is conferred in this article related to Anesthesia drug. The amount of anesthesia given to the patient depends upon the physiological parameters (i.e. electromyography, electrocardiography, electroencephalography) and evaluated by bispectrality index scale, entropy is scrutinized to achieve the goal of anesthesia. It describes the basic terminologies of anesthesia used in a different type of surgery and treatments. It briefly explains the role and classification of anesthesia drugs and their side effect. At last, the Artificial Intelligence (AI) modeling and control of anesthesia are thoroughly reviewed. The use of variables such as electroencephalogram, Bi Spectral Index due to automated monitoring tools controlled by using treatment helps the anesthesiologist. The discussion for practical anesthesiologist are implied with AI classifications with their limitations in clinical care usage. It focuses on a keen overview of the topic based on the research of anesthesia in various types, functions, models, stages, approaches, applications, and performances.

Automated summary

This article discusses the vital role of engineers in the biomedical field, particularly in medical diagnosis related to anesthesia drugs. It provides detailed information on the determination of anesthesia dosage and the effects and side effects of anesthesia drugs. Additionally, it reviews the use and limitations of artificial intelligence in anesthesia.