Reference Based Study On Sustainable Solutions In Some Sectors Using AI And ML

Abstract

To demonstrate some specifics for disease diagnosis/classification there are two different techniques used in the classification of these diseases including using "Artificial Neural Networks (ANN) and Bayesian Networks (BN)". It was found that ANN was better and could more accurately classify diabetes and CVD. Through the use of Medical Learning Classifiers (MLC's), Artificial Intelligence has been able to substantially aid doctors in patient diagnosis through the manipulation of mass Electronic Health Records (EHR's). Medical conditions have grown more complex, and with a vast history of electronic medical records building, the likelihood of case duplication is high. Although someone today with a rare illness is less likely to be the only person to have had any given disease, the inability to access cases from similarly symptomatic origins is a major roadblock for physicians. The implementation of AI to not only help find similar cases and treatments, such as through early predictors of Alzheimer’s disease and dementias, but also factor in chief symptoms and help the physicians ask the most appropriate questions helps the patient receive the most accurate diagnosis and treatment possible. This paper presents a literature based study on sustainabile solutions in Healthcare using AI and ML