title: Leveraging Expert Knowledge to Improve Machine-Learned Decision Support Systems.
abstract: 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.
authors: University of Wisconsin, Madison, USA.
authors: Finn
authors: F
authors: Kuusisto
authors: University of Porto, Porto, Portugal.
authors: Inês
authors: I
authors: Dutra
authors: University of Wisconsin, Madison, USA.
authors: Mai
authors: M
authors: Elezaby
authors: University of Wisconsin, Madison, USA.
authors: Eneida A
authors: EA
authors: Mendonça
authors: University of Wisconsin, Madison, USA.
authors: Jude
authors: J
authors: Shavlik
authors: University of Wisconsin, Madison, USA.
authors: Elizabeth S
authors: ES
authors: Burnside