Leveraging Expert Knowledge to Improve Machine-Learned Decision Support Systems.
Finn Kuusisto, Inês Dutra, Mai A. Elezaby, Eneida A. Mendonça, JUDE W. SHAVLIK, Elizabeth S. Burnside · PubMed · 2015
While the use of machine learning methods in clinical decision support has great potential for improving patient care, acquiring standardized, complete, and sufficient training data presents a major challenge for methods relying exclusively on machine learning techniques. Domain experts possess knowledge that can address these challenges and guide model development. We present Advice-Based-Learning (ABLe), a framework for incorporating expert clinical knowledge into machine learning models, and show results for an example task: estimating the probability of malignancy following a non-definitive breast core needle biopsy. By applying ABLe to this task, we demonstrate a statistically significant improvement in specificity (24.0% with p=0.004) without missing a single malignancy.