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DATE
February 26
TIME
12:00 pm - 1:00 pm EST

Venue

Online

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Webinar Wednesday: Knowledge Graphs for Explainable-AI (XAI): Explaining Machine Learning Models for Predicting Organ Transplant Survival

Details

DATE
February 26
TIME
12:00 pm - 1:00 pm EST

Venue

Online

We present a novel Neural-Symbolic Explainable-AI (XAI) framework, integrating state-of-the art semantic knowledge graphs and machine learning (ML) methods, to make the output of ML models transparent so they can be safely used in clinical settings. Current XAI methods explain the output of ML models simply in terms of feature importance. Our XAI framework generates health knowledge-driven decision paths, comprising clinical concepts and evidence drawn from the literature, to provide a clinically-interpretable trace of how the ML model has processed the input data to generate its output/predictions. We applied our XAI framework for organ transplantation decision support, where we generate and visualize decision paths comprising organ transplant concepts to explain the ML-model’s predictions of kidney transplant survival and donor-recipient matches, thus making complex ML models useful for organ transplantation.

Speakers