An Empirical Study Concerning the Impact of Perceived Usefulness and Ease of Use on the Adoption of AI-Empowered Medical Applications

In this paper, we explore multiple theoretical frameworks to understand and predict user behavior concerning the adoption of innovative, AI-empowered technologies in healthcare. Specifically, our research centers on evaluating the potential adoption rate of AI-empowered medical applications among physicians. To provide empirical support for our investigation, we carried out a comprehensive study employing questionnaires that were disseminated to a practicing medical doctors and medical students. Our methodological framework incorporates two key theories: the Technology Acceptance Model (TAM) and the Diffusion of Innovation Theory (DOI). Utilizing these theories allows us to examine critical factors that influence physicians' willingness to adopt new technologies, such as perceived ease of use and perceived usefulness. Through a nuanced understanding of doctors' perceptions and attitudes toward AI, our research aims to craft targeted strategies that could enhance the rate of adoption for these cutting-edge medical technologies. The overarching goal is to accelerate the integration of AI applications into clinical practice, thereby improving healthcare outcomes and operational efficiencies.