Prototype Link

Description

Experts: We got in touch with 2 experts; one from the Department of Radiation Oncology and another from the Emergency Department. We found these 2 departments critical when it comes to mishaps arising due to personal biases. Hence, we felt them as our appropriate audience.

Walkthrough: Since our solution lies in between the Abstract and Grounded realms, we wanted to do a prototype walkthrough in order to get feedback about each of the stages of our solution. In the walkthrough, we explained each step to the experts and at the end of the entire walkthrough, we asked for their comments. This allowed us to get retrospective feedback from our experts as they pointed out the shortcomings and the strengths of our solution design.

Feedback: We received both positive and negative feedback from both of our experts and their willingness to accept the solution varied. Our expert from the Department of Radiation Oncology was really enthusiastic about our solution and he found it really helpful to be aware of the biases which creep in while outlining the 'potential' path of the expanding tumour. Whereas, on the other hand, our expert from the Emergency Department pointed out the immense complexity of applying a potential bias system in Emergency Medicine as it would have to do with clustering and association from various inputs like patient responses, vital sign readings, patient health history, Electronic Health Record, Doctor-Patient history etc.

Takeaways: To draw associations among various inputs in Emergency Medicine will be excruciatingly complicated and has multiple points of failure. The only prospective solution would be to draw associations from just the vital signs which are objective and easy to handle. but our expert pointed out that such tools already exist and we thought our solution would lose its novel edge. On the other hand, for showing potential hypothetical pathways for the tumour to expand in Radiation Oncology, a model can work on the huge datasets of just images to draw inferences and posit alternative routes the tumour could take. This could seamlessly integrate into the physician's workflow potentially also not affecting his cognitive load.