4 citations · 15 across the 7 of their papers we have counts for
7 papers
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…
(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…
A Factored Generalized Additive Model for Clinical Decision Support in the Operating Room
Zhicheng Cui, Bradley A Fritz, Christopher R King +2
Logistic regression (LR) is widely used in clinical prediction because it is simple to deploy and easy to interpret. Nevertheless, being a linear model, LR has limited expressive c…
Assessing method agreement for paired repeated binary measurements administered by multiple raters
Wei Wang, Nan Lin, Jordan D. Oberhaus +1
Method comparison studies are essential for development in medical and clinical fields. These studies often compare a cheaper, faster, or less invasive measuring method with a wide…