Research On Factors Influencing Doctors’ Adoption Of Artificial Intelligence Imaging-assisted Diagnostic System

The “epidemic black swan” provides accelerated test scenarios for medical artificial intelligence(AI)and promotes the implementation of AI+ medical scenarios.As an AI application with great development potential,artificial intelligence imagingassisted diagnostic system can reduce the misdiagnosis rate of doctors,improve the work efficiency and service quality of doctors,alleviate the shortage of medical resources,and inject impetus into precision medicine and personalized medicine.However,owing to the lack of algorithm transparency,data security risks,uncertain medical responsibilities,and substitution threats,doctors remain resistant to the application of artificial intelligence imaging-assisted diagnostic system.Based on the current situation,this study focuses on the factors influencing doctors’ intention to adopt artificial intelligence imaging-assisted diagnostic system,to explore the behavioral evolution of doctors’ adoption intention of artificial intelligence imaging-assisted diagnostic system,and to facilitate the application of artificial intelligence imaging-assisted diagnostic system.Firstly,this study compared and summarised the relevant literature,taken the unified theory of acceptance and use of technology(UTAUT)as the theoretical basis,considered the application characteristics of artificial intelligence imaging-assisted diagnosis systems,incorporated the formation and mechanism of human-computer trust,and constructed a research model of doctors’ intention to adopt artificial intelligence imaging-assisted diagnosis system.Secondly,this study conducted a questionnaire design based on the study variables,using a combination of online and offline methods to collect 406 valid sample data.The study then used SPSS 22.0 and Amos 23.0 to conduct an empirical test of the research model based on structural equation model(SEM)to explore the effect of individual factors on doctors’ adoption intention.Finally,this study used fuzzy-set qualitative comparative analysis(fsQCA)to explore the impact of different combinations of influencing factors on doctors’ intention to adopt.The results of the SEM analysis showed that:(1)performance expectancy,effort expectancy,social influence and human-computer trust all positively influenced doctors’ adoption intention of artificial intelligence imaging-assisted diagnosis system;(2)effort expectancy could influence doctors’ adoption intention of artificial intelligence imagingassisted diagnosis system through the mediating role of performance expectancy;(3)performance expectancy,effort expectancy and social influence could influence doctors’ adoption intention of artificial intelligence imaging-assisted diagnosis system through the mediating role of human-computer trust;and(4)performance expectancy and humancomputer trust played a chain mediation role between effort expectancy and doctors’ adoption intention of artificial intelligence imaging-assisted diagnosis system.The results of the fsQCA analysis showed that performance expectancy,effort expectancy,social influence,human-machine trust and education constituted 3configurations that had an impact on the adoption of artificial intelligence imagingassisted diagnostic systems by doctors.The 3 conditional configurations are:(1)performance expectancy * effort expectancy * social influence;(2)effort expectancy *social influence * human-computer trust;and(3)performance expectancy * social influence * human-computer trust * education.Based on the results of the SEM and fsQCA studies,this study proposes the following three countermeasures and recommendations for the promotion and application of artificial intelligence image-assisted diagnosis system.First,service developers should focus on the performance expectancy and effort expectancy of doctors for artificial intelligence imaging-assisted diagnosis system.Second,hospital administrators could adjust their management strategies to augment the trust and acceptance of artificial intelligence imaging-assisted diagnosis system among doctors.Third,the government could amplify publicity on artificial intelligence imaging-assisted diagnosis system and enhance its social influence.Figure [8] Table [17] Reference [128]...