Bridging the Gap: Assessing the Integration of Artificial Intelligence in Healthcare for Improved Efficiency and Doctor Adaptability.

Abstract

Abstract The premise behind implementing artificial intelligence in healthcare comes from the initiative that aims towards improving the healthcare standards, services, and accessibilities in a time and cost-efficient manner. The conceptual framework is based on the null hypothesis which states that there is no relationship between implementing artificial intelligence in healthcare and doctor’s redundancy. Having used the 2-tailed One-Sample T-Test to test that hypothesis on IBM SPSS, in order to successfully reject the hypothesis, and present an alternatively more accurate hypothesis that is more accurately representative. Additionally, DICE framework has also been presented in order to calculate the success/failure likelihoods of implementing artificial intelligence in healthcare. We conclude that artificial intelligence significantly impacts cost reduction in the long term, as well as only ever displacing behind-the-curve doctors who are unwilling to broaden their knowledge and develop their skills. Finally, we conclude that people’s resistance to change significantly affects the efficient and effective implementation of artificial intelligence in healthcare.