Comprehensive Visualization of AI Decisions for Early Complication Detection of Cardiac Surgery Patients

Abstract

Background: Postoperative care of cardiac surgery patients is complex and often fraught with an increased morbidity and mortality due to potential complications. Even with intensive and continuous monitoring of patients it is often difficult to interpret the early signs of life-threatening complications from the vast amount of monitoring data before actual symptoms occur. AI-based monitoring systems can assist medical personal by predicting incipient complications in an early stage, which gains valuable time for treatment. Although the trend in medical AI systems is going toward the use of explainable AI models, the results and type of explanations vary widely and are hard to understand. We introduce a novel dashboard system that interprets the AI decisions and visualizes them in a uniform and comprehensible way, tailored toward medical personal.

Ähnliche Arbeiten