Development of an AI Web Application to Train Radiologists in Deep Learning
In current news, the topic of AI is more present than ever. Accordingly, new studies on the subject are constantly being published. Similarly, the topic is also gaining more and more significance in digital healthcare. However, not everybody is prepared to work with the new technology. Based on this, a web application should be developed in this work to make radiologists ""AI-ready"". For this reason, the state of the art is first discussed by presenting studies that deal with AI and radiologists. These illustrate the current state of knowledge and how radiologists see the future with AI. Especially, is shown which methods already exist to prepare them for this new technology. In the second part, currently existing web applications are presented and critically evaluated. Also included a work that developed a neural network for predicting pneumothorax disease. Next, a survey is conducted within the thesis to provide an overview of how easy it is for entry-level enthusiastic radiologists to learn about AI. Based on the findings, an analysis is carried out, which underlines the need for a practical solution for radiologists to be prepared for the daily routine with AI in the future. Then the concept is described how the application should look like to cover all requirements. Afterwards, the result of the implementation is presented. For this purpose, screenshots of developed application are shown and explanations are given how it was implemented. Subsequently, a user study of the application was also conducted to evaluate the result. The resulting outcomes are also presented. Finally, we critically reflect on whether the requirements have been met and whether the developed application serves its purpose. Furthermore, an outlook is given in which areas improvements can still be made.
Darmstadt, TU, Master Thesis, 2021