The project's funding has ended. What were the objectives and project results?
Pradtke: The goal was to implement a pilot operation with a prototype in the facilities to measure the quality we can achieve with the new mechanism and continue to optimize it. We created a prototype, used it in the healthcare facilities and collected feedback from early users.
From this vantage point, we already reached an objective we intended to achieve. Having said that, I also want to be transparent and point out that we had hoped to be further along at this stage from an algorithmic perspective. One reason for the shortfall was the onset of the COVID-19 pandemic in 2020, which prompted clinical facilities to primarily focus on infection prevention for about three months. We lost this time in our research, causing us to miss our targets towards the end.
Yet this also made us realize we must lay a much firmer foundation to build a successful machine learning model. These are exciting but also challenging processes one must go through to gain the insights needed to progressively implement AI in this setting. You achieve success on this path because you learn things you would otherwise not have learned or realized you had to understand to move forward. We are very happy we have already progressed this far.
We are also determined to continue the project along this trajectory, preferably with full funding because we are certain to have laid the groundwork for excellent future systems.