26 citations · 69 across the 10 of their papers we have counts for
5 papers · 1 filter
Prototype-Anchored Learning for Learning with Imperfect Annotations
Xiong Zhou, Xianming Liu, Deming Zhai +3
The success of deep neural networks greatly relies on the availability of large amounts of high-quality annotated data, which however are difficult or expensive to obtain. The resu…
Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang +2
Robust loss functions are essential for training deep neural networks with better generalization power in the presence of noisy labels. Symmetric loss functions are confirmed to be…
ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context
Liantao Ma, Chaohe Zhang, Yasha Wang +6
Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics. Most deep learning-based so…
AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration
Liantao Ma, Junyi Gao, Yasha Wang +6
Deep learning-based health status representation learning and clinical prediction have raised much research interest in recent years. Existing models have shown superior performanc…
Multimodal Machine Learning for Automated ICD Coding
Keyang Xu, Mike Lam, Jingzhi Pang +9
This study presents a multimodal machine learning model to predict ICD-10 diagnostic codes. We developed separate machine learning models that can handle data from different modali…