The Utilization of Artificial Intelligence in Healthcare and Its Accuracy in Medical Decision-Making

Abstract

Background: Several research studies conducted on the accuracy of machine learning and NLP in disease screening tests, disease diagnosis, predicting survival prognosis and disease complication have shown a higher accuracy and precision of AI in clinical decision-making. Methods: A review of the current English literature in PubMed revealed a number of studies on the use and accuracy of AI technology in healthcare decision-making, specifically pertaining to disease screening tests, disease diagnosis, survival prognosis and disease complication. These peer-reviewed studies were summarized and the accuracy of AI application in medical decision-making was evaluated. Results:. Research studies have shown increased accuracy in the utilization on AI in disease screening tests, disease diagnosis and predicting survival prognosis and disease complication. Conclusion: Research studies on the utilization on AI in disease screening tests, disease diagnosis as well as in predicting survival prognosis and disease complication revealed higher accuracy rates among AI systems, with accuracy rates above 75%.