18 citations · 56 across the 4 of their papers we have counts for
4 papers
Mind the Performance Gap: Examining Dataset Shift During Prospective Validation
Erkin Ötleş, Jeeheh Oh, Benjamin Li +8
Once integrated into clinical care, patient risk stratification models may perform worse compared to their retrospective performance. To date, it is widely accepted that performanc…
Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series
Jeeheh Oh, Jiaxuan Wang, Shengpu Tang +2
Recurrent neural networks (RNNs) are commonly applied to clinical time-series data with the goal of learning patient risk stratification models. Their effectiveness is due, in part…
Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks
Jeeheh Oh, Jiaxuan Wang, Jenna Wiens
Recently, researchers have started applying convolutional neural networks (CNNs) with one-dimensional convolutions to clinical tasks involving time-series data. This is due, in par…
Learning Credible Models
Jiaxuan Wang, Jeeheh Oh, Haozhu Wang +1
In many settings, it is important that a model be capable of providing reasons for its predictions (i.e., the model must be interpretable). However, the model's reasoning may not c…