Human attention maps for text classification: Do humans and neural networks focus on the same words? C Sen, T Hartvigsen, B Yin, X Kong, E Rundensteiner Proceedings of the 58th annual meeting of the association for computational …, 2020 | 73* | 2020 |
Adverse drug event detection from electronic health records using hierarchical recurrent neural networks with dual-level embedding S Wunnava, X Qin, T Kakar, C Sen, EA Rundensteiner, X Kong Drug safety 42, 113-122, 2019 | 60 | 2019 |
Adaptive-halting policy network for early classification T Hartvigsen, C Sen, X Kong, E Rundensteiner Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 51 | 2019 |
Time-aware transformer-based network for clinical notes series prediction D Zhang, J Thadajarassiri, C Sen, E Rundensteiner Machine learning for healthcare conference, 566-588, 2020 | 40 | 2020 |
Early Prediction of MRSA Infections using Electronic Health Records. T Hartvigsen, C Sen, S Brownell, E Teeple, X Kong, EA Rundensteiner HEALTHINF, 156-167, 2018 | 24 | 2018 |
Recurrent halting chain for early multi-label classification T Hartvigsen, C Sen, X Kong, E Rundensteiner Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 20 | 2020 |
Crest-risk prediction for clostridium difficile infection using multimodal data mining C Sen, T Hartvigsen, E Rundensteiner, K Claypool Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 15 | 2017 |
SVM-based sketch recognition: which hyperparameter interval to try? KT Yesilbek11, C Sen11, S Cakmak11, TM Sezgin | 9 | 2015 |
From extreme multi-label to multi-class: A hierarchical approach for automated icd-10 coding using phrase-level attention C Sen, B Ye, J Aslam, A Tahmasebi arXiv preprint arXiv:2102.09136, 2021 | 6 | 2021 |
Patient-level classification on clinical note sequences guided by attributed hierarchical attention C Sen, T Hartvigsen, X Kong, E Rundensteiner 2019 IEEE International Conference on Big Data (Big Data), 930-939, 2019 | 6 | 2019 |
Human-like explanation for text classification with limited attention supervision D Zhang, C Sen, J Thadajarassiri, T Hartvigsen, X Kong, E Rundensteiner 2021 ieee international conference on big data (big data), 957-967, 2021 | 4 | 2021 |
Clinical Performance Evaluation of a Machine Learning System for Predicting Hospital-Acquired Clostridium Difficile Infection. E Teeple, T Hartvigsen, C Sen, KT Claypool, EA Rundensteiner HEALTHINF, 656-663, 2020 | 4 | 2020 |
Comparing general and locally-learned word embeddings for clinical text mining J Thadajarassiri, C Sen, T Hartvigsen, X Kong, E Rundensteiner 2019 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2019 | 3 | 2019 |
Learning Similarity-Preserving Meta-Embedding for Text Mining J Thadajarassiri, C Sen, T Hartvigsen, X Kong, E Rundensteiner 2020 IEEE International Conference on Big Data (Big Data), 808-817, 2020 | 2 | 2020 |
Learning to Selectively Update State Neurons in Recurrent Networks T Hartvigsen, C Sen, X Kong, E Rundensteiner Proceedings of the 29th ACM International Conference on Information …, 2020 | 2 | 2020 |
Detecting MRSA infections by fusing structured and unstructured electronic health record data T Hartvigsen, C Sen, EA Rundensteiner Biomedical Engineering Systems and Technologies: 11th International Joint …, 2019 | 2 | 2019 |
Handling Missing Values in Multivariate Time Series Classification* J Friend, A Hauck, S Kurada, T Hartvigsen, C Sen, EA Rundensteiner 2018 IEEE MIT Undergraduate Research Technology Conference (URTC), 1-3, 2018 | 1 | 2018 |
SVM for sketch recognition: Which hyperparameter interval to try? KT Yesilbek, C Sen, S Cakmak, TM Sezgin 2015 23nd Signal Processing and Communications Applications Conference (SIU …, 2015 | 1 | 2015 |
Attention-based Deep Learning Models for Text Classification and their Interpretability C Sen IBM Research, 2020 | | 2020 |
Learning Temporal Relevance in Longitudinal Medical Notes C Sen, T Hartvigsen, X Kong, E Rundensteiner 2019 IEEE International Conference on Big Data (Big Data), 2474-2483, 2019 | | 2019 |