380 citations · 1.2k across the 32 of their papers we have counts for
33 papers
Outlier detection for patient monitoring and alerting
Miloš Hauskrecht, Iyad Batal, Michal Valko +3
We develop and evaluate a data-driven approach for detecting unusual (anomalous) patient-management decisions using past patient cases stored in electronic health records (EHRs). O…
Conditional outlier detection for clinical alerting
Milos Hauskrecht, Michal Valko, Shyam Visweswaran +3
We develop and evaluate a data-driven approach for detecting unusual (anomalous) patient-management actions using past patient cases stored in an electronic health record (EHR) sys…
Evidence-based anomaly detection in clinical domains
Milos Hauskrecht, Michal Valko, Branislav Kveton +2
Anomaly detection methods can be very useful in identifying interesting or concerning events. In this work, we develop and examine new probabilistic anomaly detection methods that…
Conditional anomaly detection using soft harmonic functions: An application to clinical alerting
Michal Valko, Hamed Valizadegan, Branislav Kveton +2
Timely detection of concerning events is an important problem in clinical practice. In this paper, we consider the problem of conditional anomaly detection that aims to identify da…
Conditional anomaly detection with soft harmonic functions
Michal Valko, Branislav Kveton, Hamed Valizadegan +2
In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label. We develop a new non-paramet…
Learning Latent Causal Structures with a Redundant Input Neural Network
Jonathan D. Young, Bryan Andrews, Gregory F. Cooper +1
Most causal discovery algorithms find causal structure among a set of observed variables. Learning the causal structure among latent variables remains an important open problem, pa…