12 citations · 21 across the 3 of their papers we have counts for
5 papers
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data
Benjamin Shickel, Parisa Rashidi
Deep learning continues to revolutionize an ever-growing number of critical application areas including healthcare, transportation, finance, and basic sciences. Despite their incre…
Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension
Shounak Datta, Tyler J. Loftus, Matthew M. Ruppert +12
To test the hypothesis that accuracy, discrimination, and precision in predicting postoperative complications improve when using both preoperative and intraoperative data input fea…
The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring
Anis Davoudi, Kumar Rohit Malhotra, Benjamin Shickel +8
Currently, many critical care indices are repetitively assessed and recorded by overburdened nurses, e.g. physical function or facial pain expressions of nonverbal patients. In add…
DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning
Benjamin Shickel, Tyler J. Loftus, Lasith Adhikari +3
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static…
Hashtag Healthcare: From Tweets to Mental Health Journals Using Deep Transfer Learning
Benjamin Shickel, Martin Heesacker, Sherry Benton +1
As the popularity of social media platforms continues to rise, an ever-increasing amount of human communication and self- expression takes place online. Most recent research has fo…