11 citations · 16 across the 6 of their papers we have counts for
7 papers
Facilitating Change Implementation for Continuous ML-Safety Assurance
Chih-Hong Cheng, Nguyen Anh Vu Doan, Balahari Balu +9
We propose a method for deploying a safety-critical machine-learning component into continuously evolving environments where an increased degree of automation in the engineering pr…
Description-based Label Attention Classifier for Explainable ICD-9 Classification
Malte Feucht, Zhiliang Wu, Sophia Althammer +1
ICD-9 coding is a relevant clinical billing task, where unstructured texts with information about a patient's diagnosis and treatments are annotated with multiple ICD-9 codes. Auto…
Categorical EHR Imputation with Generative Adversarial Nets
Yinchong Yang, Zhiliang Wu, Volker Tresp +1
Electronic Health Records often suffer from missing data, which poses a major problem in clinical practice and clinical studies. A novel approach for dealing with missing data are…
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models
Zhiliang Wu, Yinchong Yang, Peter A. Fasching +1
Recurrent neural network based solutions are increasingly being used in the analysis of longitudinal Electronic Health Record data. However, most works focus on prediction accuracy…
Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning
Zhiliang Wu, Yinchong Yang, Jindong Gu +1
Deep neural networks are increasingly being used for the analysis of medical images. However, most works neglect the uncertainty in the model's prediction. We propose an uncertaint…
Introspective Learning by Distilling Knowledge from Online Self-explanation
Jindong Gu, Zhiliang Wu, Volker Tresp
In recent years, many explanation methods have been proposed to explain individual classifications of deep neural networks. However, how to leverage the created explanations to imp…