Dynamic measurement scheduling for event forecasting using deep RL
CH Chang, M Mai… - … Conference on Machine …, 2019 - proceedings.mlr.press
Imagine a patient in critical condition. What and when should be measured to forecast
detrimental events, especially under the budget constraints? We answer this question by …
detrimental events, especially under the budget constraints? We answer this question by …
Context-aware and time-aware attention-based model for disease risk prediction with interpretability
Thanks to the huge accumulation of Electronic Health Records (EHRs), numerous deep
learning based predictive models were proposed for this task. Among them, most of the …
learning based predictive models were proposed for this task. Among them, most of the …
Incorporating medical code descriptions for diagnosis prediction in healthcare
Background Diagnosis aims to predict the future health status of patients according to their
historical electronic health records (EHR), which is an important yet challenging task in …
historical electronic health records (EHR), which is an important yet challenging task in …
[BUCH][B] A variational recurrent adversarial multi-source domain adaptation framework for septic shock early prediction across medical systems
F Khoshnevisan - 2021 - search.proquest.com
Sepsis is a leading cause of death and a major challenge in US hospitals. Septic shock, the
most severe complication of sepsis, has a mortality rate of 50%. However, as many as 80 …
most severe complication of sepsis, has a mortality rate of 50%. However, as many as 80 …