4 citations · 10 across the 6 of their papers we have counts for
6 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…
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…
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…
(Un)fairness in Post-operative Complication Prediction Models
Sandhya Tripathi, Bradley A. Fritz, Mohamed Abdelhack +3
With the current ongoing debate about fairness, explainability and transparency of machine learning models, their application in high-impact clinical decision-making systems must b…
Time-Variant Graph Classification
Haishuai Wang
Graphs are commonly used to represent objects, such as images and text, for pattern classification. In a dynamic world, an object may continuously evolve over time, and so does the…