Successes and Misses of Global Health Development: Detecting Temporal Concept Drift of Under-5 Mortality Prediction Models with Bias ScanIfrah IdreesSkyler Speakmanet al.2021AMIA Informatics Summit 2021
Data-level Linkage of Multiple Surveys for Improved Understanding of Global Health ChallengesGirmaw Abebe TadesseCelia Cintaset al.2021AMIA Informatics Summit 2021
Inspection of blackbox models for evaluating vulnerability in maternal, newborn, and child healthWilliam OgalloSkyler Speakmanet al.2021IJCAI 2020
Detecting adversarial attacks via subset scanning of autoencoder activations and reconstruction errorCelia CintasSkyler Speakmanet al.2021IJCAI 2020
Successes and Misses of Global Health Development: Detecting Temporal Concept Drift of Under-5 Mortality Prediction Models with Bias ScanIfrah IdreesSkyler Speakmanet al.2021AMIA Annual Symposium
Unsupervised Discovery of Subgroups with Anomalous Maternal and Neonatal Outcomes with WHO’s Safe Childbirth Checklist as InterventionGirmaw Abebe TadesseWilliam Ogalloet al.2020NeurIPS 2020
Identifying Audio Adversarial Examples via Anomalous Pattern DetectionVictor AkinwandeCelia Cintaset al.2020KDD 2020
Prediction of neonatal mortality in Sub-Saharan African countries using data-level linkage of multiple surveysGirmaw Abebe TadesseCelia Cintaset al.2020ICML 2020
Cross-country linkage of disjoint datasets to address global health challengesGirmaw Abebe TadesseCelia Cintaset al.2021IJCAI 2020
Preservation of anomalous subgroups on variational autoencoder transformed dataSamuel C. MainaReginald Bryantet al.2020ICASSP 2020