title: Improving the radiologist-CAD interaction: designing for appropriate trust.
abstract: Computer-aided diagnosis (CAD) has great potential to improve radiologists' diagnostic performance. However, the reported performance of the radiologist-CAD team is lower than what might be expected based on the performance of the radiologist and the CAD system in isolation. This indicates that the interaction between radiologists and the CAD system is not optimal. An important factor in the interaction between humans and automated aids (such as CAD) is trust. Suboptimal performance of the human-automation team is often caused by an inappropriate level of trust in the automation. In this review, we examine the role of trust in the radiologist-CAD interaction and suggest ways to improve the output of the CAD system so that it allows radiologists to calibrate their trust in the CAD system more effectively. Observer studies of the CAD systems show that radiologists often have an inappropriate level of trust in the CAD system. They sometimes under-trust CAD, thereby reducing its potential benefits, and sometimes over-trust it, leading to diagnostic errors they would not have made without CAD. Based on the literature on trust in human-automation interaction and the results of CAD observer studies, we have identified four ways to improve the output of CAD so that it allows radiologists to form a more appropriate level of trust in CAD. Designing CAD systems for appropriate trust is important and can improve the performance of the radiologist-CAD team. Future CAD research and development should acknowledge the importance of the radiologist-CAD interaction, and specifically the role of trust therein, in order to create the perfect artificial partner for the radiologist. This review focuses on the role of trust in the radiologist-CAD interaction. The aim of the review is to encourage CAD developers to design for appropriate trust and thereby improve the performance of the radiologist-CAD team.
authors.affiliation: Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands. Electronic address: w.jorritsma01@umcg.nl.
authors.forename: W
authors.initials: W
authors.lastname: Jorritsma
authors.affiliation: Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, Nijenborgh 9, 9747 AG, Groningen, The Netherlands.
authors.forename: F
authors.initials: F
authors.lastname: Cnossen
authors.affiliation: Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands; Center for Medical Imaging North East Netherlands, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.
authors.forename: P M A
authors.initials: PM
authors.lastname: van Ooijen
mesh_terms: D001292:Attitude to Computers; D006801:Humans; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011871:Radiology / Q000379:methods*; D015203:Reproducibility of Results; D035502:Trust