4 citations · 11 across the 10 of their papers we have counts for
11 papers · 1 filter
Universal EHR Federated Learning Framework
Junu Kim, Kyunghoon Hur, Seongjun Yang +1
Federated learning (FL) is the most practical multi-source learning method for electronic healthcare records (EHR). Despite its guarantee of privacy protection, the wide applicatio…
Lead-agnostic Self-supervised Learning for Local and Global Representations of Electrocardiogram
Jungwoo Oh, Hyunseung Chung, Joon-myoung Kwon +2
In recent years, self-supervised learning methods have shown significant improvement for pre-training with unlabeled data and have proven helpful for electrocardiogram signals. How…
Natural Attribute-based Shift Detection
Jeonghoon Park, Jimin Hong, Radhika Dua +4
Despite the impressive performance of deep networks in vision, language, and healthcare, unpredictable behaviors on samples from the distribution different than the training distri…
Evaluation of Out-of-Distribution Detection Performance of Self-Supervised Learning in a Controllable Environment
Jeonghoon Park, Kyungmin Jo, Daehoon Gwak +3
We evaluate the out-of-distribution (OOD) detection performance of self-supervised learning (SSL) techniques with a new evaluation framework. Unlike the previous evaluation methods…
Neural Ordinary Differential Equations for Intervention Modeling
Daehoon Gwak, Gyuhyeon Sim, Michael Poli +3
By interpreting the forward dynamics of the latent representation of neural networks as an ordinary differential equation, Neural Ordinary Differential Equation (Neural ODE) emerge…
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer
Edward Choi, Zhen Xu, Yujia Li +4
Effective modeling of electronic health records (EHR) is rapidly becoming an important topic in both academia and industry. A recent study showed that using the graphical structure…