Artikel dengan mandat akses publik - Elke RundensteinerPelajari lebih lanjut
Tidak tersedia di mana pun: 33
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
Mandat: US Institute of Education Sciences
Screening for depression with retrospectively harvested private versus public text
ML Tlachac, E Rundensteiner
IEEE journal of biomedical and health informatics 24 (11), 3326-3332, 2020
Mandat: US Department of Education
Depression screening from text message reply latency
ML Tlachac, EA Rundensteiner
2020 42nd annual international conference of the IEEE engineering in …, 2020
Mandat: US Department of Education
Emu: Early mental health uncovering framework and dataset
ML Tlachac, E Toto, J Lovering, R Kayastha, N Taurich, E Rundensteiner
2021 20th IEEE international conference on machine learning and applications …, 2021
Mandat: US National Science Foundation, US Department of Education
Mobile depression screening with time series of text logs and call logs
ML Tlachac, V Melican, M Reisch, E Rundensteiner
2021 IEEE EMBS international conference on biomedical and health informatics …, 2021
Mandat: US National Science Foundation, US Department of Education
Screening for suicidal ideation with text messages
ML Tlachac, K Dixon-Gordon, E Rundensteiner
2021 IEEE EMBS International Conference on Biomedical and Health Informatics …, 2021
Mandat: US Department of Education
Early mental health uncovering with short scripted and unscripted voice recordings
ML Tlachac, R Flores, E Toto, E Rundensteiner
Deep Learning Applications, Volume 4, 79-110, 2022
Mandat: US National Science Foundation, US Department of Education
Transfer learning for depression screening from follow-up clinical interview questions
R Flores, ML Tlachac, E Toto, E Rundensteiner
Deep Learning Applications, Volume 4, 53-78, 2022
Mandat: US National Science Foundation, US Department of Education
Topological data analysis to engineer features from audio signals for depression detection
ML Tlachac, A Sargent, E Toto, R Paffenroth, E Rundensteiner
2020 19th IEEE International Conference on Machine Learning and Applications …, 2020
Mandat: US National Science Foundation, US Department of Education
Depression screening using deep learning on follow-up questions in clinical interviews
R Flores, ML Tlachac, E Toto, EA Rundensteiner
2021 20th IEEE International Conference on Machine Learning and Applications …, 2021
Mandat: US National Science Foundation, US Department of Education
Gan for generating user-specific human activity data from an incomplete training corpus
W Gerych, H Kim, J DeOliveira, MC Martin, L Buquicchio, ...
2021 IEEE International Conference on Big Data (Big Data), 4705-4714, 2021
Mandat: US National Science Foundation, US Department of Defense
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
Mandat: US National Science Foundation, US Department of Education
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
Mandat: US National Science Foundation, US Department of Education
Corrosion assessment: Data mining for quantifying associations between indoor accelerated and outdoor natural tests
B Yin, TA Considine, F Emdad, JV Kelley, RE Jensen, EA Rundensteiner
2020 IEEE International Conference on Big Data (Big Data), 2929-2936, 2020
Mandat: US Department of Defense
Intosis: Interactive observation of smartphone inferred symptoms for in-the-wild data
H Mansoor, W Gerych, L Buquicchio, A Alajaji, K Chandrasekaran, E Agu, ...
2020 IEEE International Conference on Big Data (Big Data), 4882-4891, 2020
Mandat: US Department of Defense
Human context recognition: A controllable GAN approach
J DeOliveira, H Kim, MC Martin, W Gerych, E Rundensteiner
2021 IEEE MIT Undergraduate Research Technology Conference (URTC), 1-5, 2021
Mandat: US National Science Foundation
Cartman: Complex activity recognition using topic models for feature generation from wearable sensor data
K Chandrasekaran, W Gerych, L Buquicchio, A Alajaji, E Agu, ...
2021 IEEE International Conference on Smart Computing (SMARTCOMP), 39-46, 2021
Mandat: US Department of Defense
Neural network for nonlinear dimension reduction through manifold recovery
J Bader, D Nelson, T Chai-Zhang, W Gerych, E Rundensteiner
2019 IEEE MIT Undergraduate Research Technology Conference (URTC), 1-4, 2019
Mandat: US National Science Foundation
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
Mandat: US Department of Education
Adversarial human context recognition: Evasion attacks and defenses
A Alajaji, W Gerych, K Chandrasekaran, L Buquicchio, E Agu, ...
2023 IEEE 47th Annual Computers, Software, and Applications Conference …, 2023
Mandat: US Department of Defense
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