543 citations · 821 across the 7 of their papers we have counts for
7 papers
Improving Clinical Diagnosis with Counterfactual Multi-Agent Reasoning
Zhiwen You, Xi Chen, Aniket Vashishtha +5
Clinical diagnosis is a complex reasoning process in which clinicians gather evidence, form hypotheses, and test them against alternative explanations. In medical training, this re…
Forecasting adverse surgical events using self-supervised transfer learning for physiological signals
Hugh Chen, Scott Lundberg, Gabe Erion +2
Hundreds of millions of surgical procedures take place annually across the world, which generate a prevalent type of electronic health record (EHR) data comprising time series phys…
An Adversarial Approach for the Robust Classification of Pneumonia from Chest Radiographs
Joseph D. Janizek, Gabriel Erion, Alex J. DeGrave +1
While deep learning has shown promise in the domain of disease classification from medical images, models based on state-of-the-art convolutional neural network architectures often…
Improving performance of deep learning models with axiomatic attribution priors and expected gradients
Gabriel Erion, Joseph D. Janizek, Pascal Sturmfels +2
Recent research has demonstrated that feature attribution methods for deep networks can themselves be incorporated into training; these attribution priors optimize for a model whos…
Explainable AI for Trees: From Local Explanations to Global Understanding
Scott M. Lundberg, Gabriel Erion, Hugh Chen +7
Tree-based machine learning models such as random forests, decision trees, and gradient boosted trees are the most popular non-linear predictive models used in practice today, yet…
Consistent Individualized Feature Attribution for Tree Ensembles
Scott M. Lundberg, Gabriel G. Erion, Su-In Lee
Interpreting predictions from tree ensemble methods such as gradient boosting machines and random forests is important, yet feature attribution for trees is often heuristic and not…