output
20142022
most citedPopNet: Real-Time Population-Level Disease Prediction with Data Latency

7 citations

5 papers

cs.SI20227 cited

PopNet: Real-Time Population-Level Disease Prediction with Data Latency

Junyi Gao, Cao Xiao, Lucas M. Glass +1

Population-level disease prediction estimates the number of potential patients of particular diseases in some location at a future time based on (frequently updated) historical dis…

eess.IV20205 cited

FLANNEL: Focal Loss Based Neural Network Ensemble for COVID-19 Detection

Zhi Qiao, Austin Bae, Lucas M. Glass +2

To test the possibility of differentiating chest x-ray images of COVID-19 against other pneumonia and healthy patients using deep neural networks. We construct the X-ray imaging da…

cs.LG20202 cited

COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching

Junyi Gao, Cao Xiao, Lucas M. Glass +1

Clinical trials play important roles in drug development but often suffer from expensive, inaccurate and insufficient patient recruitment. The availability of massive electronic he…

cs.LG20191 cited

No-regret Non-convex Online Meta-Learning

Zhenxun Zhuang, Yunlong Wang, Kezi Yu +1

The online meta-learning framework is designed for the continual lifelong learning setting. It bridges two fields: meta-learning which tries to extract prior knowledge from past ta…

q-fin.CP2014

Semiclassical approximation in stochastic optimal control I. Portfolio construction problem

Sakda Chaiworawitkul, Patrick S. Hagan, Andrew Lesniewski

This is the first in a series of papers in which we study an efficient approximation scheme for solving the Hamilton-Jacobi-Bellman equation for multi-dimensional problems in stoch…