19 citations · 19 across the 1 of their papers we have counts for
3 papers
cs.CV2021
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays
Emma Chen, Andy Kim, Rayan Krishnan +3
A major obstacle to the integration of deep learning models for chest x-ray interpretation into clinical settings is the lack of understanding of their failure modes. In this work,…
cs.LG2020★ 19 cited
Using LSTM and SARIMA Models to Forecast Cluster CPU Usage
Langston Nashold, Rayan Krishnan
As large scale cloud computing centers become more popular than individual servers, predicting future resource demand need has become an important problem. Forecasting resource nee…
eess.IV2020
CheXphoto: 10,000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness
Nick A. Phillips, Pranav Rajpurkar, Mark Sabini +10
Clinical deployment of deep learning algorithms for chest x-ray interpretation requires a solution that can integrate into the vast spectrum of clinical workflows across the world.…