4 citations · 16 across the 8 of their papers we have counts for
8 papers
Time Associated Meta Learning for Clinical Prediction
Hao Liu, Muhan Zhang, Zehao Dong +5
Rich Electronic Health Records (EHR), have created opportunities to improve clinical processes using machine learning methods. Prediction of the same patient events at different ti…
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks
Lecheng Kong, Christopher King, Bradley Fritz +1
Learning to represent free text is a core task in many clinical machine learning (ML) applications, as clinical text contains observations and plans not otherwise available for inf…
Algorithmic Bias in Machine Learning Based Delirium Prediction
Sandhya Tripathi, Bradley A Fritz, Michael S Avidan +2
Although prediction models for delirium, a commonly occurring condition during general hospitalization or post-surgery, have not gained huge popularity, their algorithmic bias eval…
Self-explaining Hierarchical Model for Intraoperative Time Series
Dingwen Li, Bing Xue, Christopher King +4
Major postoperative complications are devastating to surgical patients. Some of these complications are potentially preventable via early predictions based on intraoperative data.…
Deep Learning to Jointly Schema Match, Impute, and Transform Databases
Sandhya Tripathi, Bradley A. Fritz, Mohamed Abdelhack +3
An applied problem facing all areas of data science is harmonizing data sources. Joining data from multiple origins with unmapped and only partially overlapping features is a prere…
A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues
Mohamed Abdelhack, Jiaming Zhang, Sandhya Tripathi +5
Data missingness and quality are common problems in machine learning, especially for high-stakes applications such as healthcare. Developers often train machine learning models on…