1 code implementation • 18 Nov 2015 • Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun
Leveraging large historical data in electronic health record (EHR), we developed Doctor AI, a generic predictive model that covers observed medical conditions and medication uses.
1 code implementation • 11 Feb 2016 • Edward Choi, Andy Schuetz, Walter F. Stewart, Jimeng Sun
Objective: To transform heterogeneous clinical data from electronic health records into clinically meaningful constructed features using data driven method that rely, in part, on temporal relations among data.
1 code implementation • NeurIPS 2016 • Edward Choi, Mohammad Taha Bahadori, Joshua A. Kulas, Andy Schuetz, Walter F. Stewart, Jimeng Sun
RETAIN was tested on a large health system EHR dataset with 14 million visits completed by 263K patients over an 8 year period and demonstrated predictive accuracy and computational scalability comparable to state-of-the-art methods such as RNN, and ease of interpretability comparable to traditional models.
Ranked #2 on Disease Trajectory Forecasting on UK CF trust
1 code implementation • 21 Nov 2016 • Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun
-Interpretation:The representations learned by deep learning methods should align with medical knowledge.
no code implementations • 8 Feb 2017 • Mohammad Taha Bahadori, Krzysztof Chalupka, Edward Choi, Robert Chen, Walter F. Stewart, Jimeng Sun
In application domains such as healthcare, we want accurate predictive models that are also causally interpretable.
3 code implementations • 19 Mar 2017 • Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F. Stewart, Jimeng Sun
Access to electronic health record (EHR) data has motivated computational advances in medical research.
no code implementations • 14 Mar 2018 • Ioakeim Perros, Evangelos E. Papalexakis, Haesun Park, Richard Vuduc, Xiaowei Yan, Christopher deFilippi, Walter F. Stewart, Jimeng Sun
We propose two variants, SUSTain_M and SUSTain_T, to handle both matrix and tensor inputs, respectively.
1 code implementation • NeurIPS 2018 • Edward Choi, Cao Xiao, Walter F. Stewart, Jimeng Sun
Deep learning models exhibit state-of-the-art performance for many predictive healthcare tasks using electronic health records (EHR) data, but these models typically require training data volume that exceeds the capacity of most healthcare systems.