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Explainable Medical Diagnostic Systems

Background​

This research theme is focused in building human-centric explainable intelligent interfaces that can assist physicians in understanding the predictions of deep learning models in the medical diagnosis of chest X-ray images.

Chest X-ray XAI

Research Topics​

This research theme aims to build a novel framework consisting of algorithms, models, techniques, and tools that i) support generating human-centric explanations from the machine learned predictions of chest X-rays, and ii) allow medical practitioners to interact with the reasoning underpinned by machine intelligence. The main research topics include but are not limited to:

  • Investigate the incorporation of human classification patterns in deep learning frameworks
  • Develop user-centric explainable intelligent user interfaces
  • Generate persuasive human-centric explanations for medical diagnosis
  • Develop new frameworks and tools to support human in the loop in medical diagnosis
  • Develop human and application grounded evaluation protocols for XAI in medical diagnosis

Publications​

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