1 citations · 2 across the 3 of their papers we have counts for
4 papers
A Domain Incremental Continual Learning Benchmark for ICU Time Series Model Transportability
Ryan King, Conrad Krueger, Ethan Veselka +2
In recent years, machine learning has made significant progress in clinical outcome prediction, demonstrating increasingly accurate results. However, the substantial resources requ…
An Efficient Contrastive Unimodal Pretraining Method for EHR Time Series Data
Ryan King, Shivesh Kodali, Conrad Krueger +2
Machine learning has revolutionized the modeling of clinical timeseries data. Using machine learning, a Deep Neural Network (DNN) can be automatically trained to learn a complex ma…
Which LLMs are Difficult to Detect? A Detailed Analysis of Potential Factors Contributing to Difficulties in LLM Text Detection
Shantanu Thorat, Tianbao Yang
As LLMs increase in accessibility, LLM-generated texts have proliferated across several fields, such as scientific, academic, and creative writing. However, LLMs are not created eq…
Multimodal Pretraining of Medical Time Series and Notes
Ryan King, Tianbao Yang, Bobak Mortazavi
Within the intensive care unit (ICU), a wealth of patient data, including clinical measurements and clinical notes, is readily available. This data is a valuable resource for compr…