PhD Defence Laurens Peter Christ Topff

Keywords: Artificial Intelligence, Radiology, Medical Imaging, Clinical use 
 

"Bridging the AI Gap in Radiology From Data to Clinical Impact"

This thesis addressed the challenges of translating artificial intelligence (AI) applications from research to clinical practice in radiology. Despite significant advances in AI research for medical imaging analysis, widespread adoption in clinical settings remains limited. The research focused on both developing robust AI models and evaluating their implementation in clinical workflows. For model development, the thesis demonstrated the importance of high-quality, diverse datasets and rigorous validation. For implementation, commercially available AI applications were evaluated in clinical workflows. The studies showed that AI tools can enhance diagnostic accuracy, for example in detecting unexpected critical findings like pulmonary embolism in cancer patients. The research emphasized that clinical domain expertise remains crucial throughout the AI development lifecycle. By addressing both technical and clinical challenges, this thesis contributes to bridging the gap between AI's promising capabilities and its successful integration into clinical practice. 

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