期刊论文详细信息
Breast
Using artificial intelligence to analyse and teach communication in healthcare
Ehsan Hoque1  Phyllis Butow2 
[1] Corresponding author. School of Psychology, Lifehouse Level 6-North (C39Z), University of Sydney, NSW 2006, Australia.;University of Sydney, School of Psychology, Centre for Medical Psychology and Evidence-Based Medicine (CeMPED), Sydney, Australia;
关键词: Artificial intelligence;    Machine learning;    Communication;    Healthcare;   
DOI  :  
来源: DOAJ
【 摘 要 】

Communication is a core component of effective healthcare that impacts many patient and doctor outcomes, yet is complex and challenging to both analyse and teach. Human-based coding and audit systems are time-intensive and costly; thus, there is considerable interest in the application of artificial intelligence to this topic, through machine learning using both supervised and unsupervised learning algorithms. In this article we introduce health communication, its importance for patient and health professional outcomes, and the need for rigorous empirical data to support this field. We then discuss historical interaction coding systems and recent developments in applying artificial intelligence (AI) to automate such coding in the health setting. Finally, we discuss available evidence for the reliability and validity of AI coding, application of AI in training and audit of communication, as well as limitations and future directions in this field. In summary, recent advances in machine learning have allowed accurate textual transcription, and analysis of prosody, pauses, energy, intonation, emotion and communication style. Studies have established moderate to good reliability of machine learning algorithms, comparable with human coding (or better), and have identified some expected and unexpected associations between communication variables and patient satisfaction. Finally, application of artificial intelligence to communication skills training has been attempted, to provide audit and feedback, and through the use of avatars. This looks promising to provide confidential and easily accessible training, but may be best used as an adjunct to human-based training.

【 授权许可】

Unknown   

  文献评价指标  
  下载次数:0次 浏览次数:1次