Peering through the shadows: Diagnostic bias and the impact on clinical decision making Imaging Adam Greenbaum

Adam Greenbaum

You will be also offered help in communicating costs to clients

and potential risks associated with AI adoption

and reflect on how the latest trends also bring challenges but don't worry

including how and when to send us your feedback

Peering through the shadows: Diagnostic bias and the impact on clinical decision making Imaging Adam GreenbaumDiagnostic bias leading to diagnostic errors is a common occurrence for all clinicians but every one of us can be blind to it and its consequences on our patients, our clients and ourselves. Examples of diagnostic bias include availability bias, anchoring bias, framing bias, confirmation bias and premature closure. In this lecture we will discuss the types of diagnostic bias that can occur in clinical practice and how they can affect clinical decision