مقاله‌های دارای تعهدات انتشار عمومی - Jenna Wiensبیشتر بدانید
جای دیگری دردسترس است: ۶۸
Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology
J Wiens, ES Shenoy
Clinical Infectious Diseases, 2017
تعهدات: US National Science Foundation, US National Institutes of Health
A framework for effective application of machine learning to microbiome-based classification problems
BD Topçuoğlu, NA Lesniak, MT Ruffin IV, J Wiens, PD Schloss
MBio 11 (3), 10.1128/mbio. 00434-20, 2020
تعهدات: US National Institutes of Health
A Generalizable, Data-Driven Approach to Predict Daily Risk of Clostridium difficile Infection at Two Large Academic Health Centers
J Oh, M Makar, C Fusco, R McCaffrey, K Rao, EE Ryan, L Washer, ...
Infection Control and Hospital Epidemiology 39 (4), 425-433, 2018
تعهدات: US National Science Foundation, US National Institutes of Health
Evaluating a widely implemented proprietary deterioration index model among hospitalized patients with COVID-19
K Singh, TS Valley, S Tang, BY Li, F Kamran, MW Sjoding, J Wiens, ...
Annals of the American Thoracic Society 18 (7), 1129-1137, 2021
تعهدات: US National Institutes of Health
Deep Multi-Output Forecasting: Learning to Accurately Predict Blood Glucose Trajectories
I Fox, L Ang, M Jaiswal, R Pop-Busui, J Wiens
KDD'18 Proceedings of the 24th ACM SIGKDD International Conference on …, 2018
تعهدات: US National Science Foundation, US National Institutes of Health
Deep reinforcement learning for closed-loop blood glucose control
I Fox, J Lee, R Pop-Busui, J Wiens
Machine Learning for Healthcare Conference, 508-536, 2020
تعهدات: Juvenile Diabetes Research Foundation
Model selection for offline reinforcement learning: Practical considerations for healthcare settings
S Tang, J Wiens
Machine Learning for Healthcare Conference, 2-35, 2021
تعهدات: US National Science Foundation, US National Institutes of Health
Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data
S Tang, P Davarmanesh, Y Song, D Koutra, MW Sjoding, J Wiens
Journal of the American Medical Informatics Association 27 (12), 1921-1934, 2020
تعهدات: US National Science Foundation, US National Institutes of Health
Machine learning for patient risk stratification for acute respiratory distress syndrome
D Zeiberg, T Prahlad, BK Nallamothu, TJ Iwashyna, J Wiens, MW Sjoding
PloS one 14 (3), e0214465, 2019
تعهدات: US National Institutes of Health, US Department of Veterans Affairs
Heart sound classification based on temporal alignment techniques
JJG Ortiz, CP Phoo, J Wiens
2016 computing in cardiology conference (CinC), 589-592, 2016
تعهدات: US National Science Foundation
Measuring the impact of AI in the diagnosis of hospitalized patients: a randomized clinical vignette survey study
S Jabbour, D Fouhey, S Shepard, TS Valley, EA Kazerooni, N Banovic, ...
JAMA 330 (23), 2275-2284, 2023
تعهدات: US National Institutes of Health
Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks
J Oh, J Wang, J Wiens
Proceedings of the 3rd Machine Learning for Health Care (MLHC), 2018
تعهدات: US National Science Foundation, US National Institutes of Health
Using Machine Learning and the Electronic Health Record to Predict Complicated Clostridium difficile Infection
BY Li, J Oh, VB Young, K Rao, J Wiens
Open forum infectious diseases 6 (5), ofz186, 2019
تعهدات: US National Institutes of Health
Deep Residual Time-Series Forecasting: Application to Blood Glucose Prediction.
H Rubin-Falcone, I Fox, J Wiens
KDH@ ECAI 20, 105-109, 2020
تعهدات: Juvenile Diabetes Research Foundation
The number needed to benefit: estimating the value of predictive analytics in healthcare
VX Liu, DW Bates, J Wiens, NH Shah
Journal of the American Medical Informatics Association 26 (12), 1655-1659, 2019
تعهدات: US National Institutes of Health
Deep learning applied to chest X-rays: exploiting and preventing shortcuts
S Jabbour, D Fouhey, E Kazerooni, MW Sjoding, J Wiens
Machine Learning for Healthcare Conference, 750-782, 2020
تعهدات: US National Science Foundation, US National Institutes of Health
Early identification of patients admitted to hospital for covid-19 at risk of clinical deterioration: model development and multisite external validation study
F Kamran, S Tang, E Otles, DS McEvoy, SN Saleh, J Gong, BY Li, S Dutta, ...
The British Medical Journal (BMJ) 376, 2022
تعهدات: US National Science Foundation, US National Institutes of Health
Learning Credible Models
J Wang, J Oh, J Wiens
KDD'18 The 24th ACM SIGKDD International Conference on Knowledge Discovery …, 2018
تعهدات: US National Science Foundation, US National Institutes of Health
Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice: JACC State-of-the-Art Review
R Khera, EK Oikonomou, GN Nadkarni, JR Morley, J Wiens, AJ Butte, ...
Journal of the American College of Cardiology 84 (1), 97-114, 2024
تعهدات: Robert Wood Johnson Foundation, Chan Zuckerberg Initiative
Characterizing heterogeneity in the progression of Alzheimer's disease using longitudinal clinical and neuroimaging biomarkers
D Goyal, D Tjandra, RQ Migrino, B Giordani, Z Syed, J Wiens, ...
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 10, 629-637, 2018
تعهدات: US National Science Foundation, US Department of Defense, US National …
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