Learning electronic health records through hyperbolic embedding of medical ontologies

Q Lu, N De Silva, S Kafle, J Cao, D Dou… - Proceedings of the 10th …, 2019 - dl.acm.org
Unplanned intensive care units (ICU) readmissions and in-hospital mortality of patients are
two important metrics for evaluating the quality of hospital care. Identifying patients with …

[HTML][HTML] Knowledge Graph Embeddings for ICU readmission prediction

RMS Carvalho, D Oliveira, C Pesquita - BMC Medical Informatics and …, 2023 - Springer
Abstract Background Intensive Care Unit (ICU) readmissions represent both a health risk for
patients, with increased mortality rates and overall health deterioration, and a financial …

Predicting clinical outcomes across changing electronic health record systems

JJ Gong, T Naumann, P Szolovits… - Proceedings of the 23rd …, 2017 - dl.acm.org
Existing machine learning methods typically assume consistency in how semantically
equivalent information is encoded. However, the way information is recorded in databases …

[HTML][HTML] Fusion of sequential visits and medical ontology for mortality prediction

K Niu, Y Lu, X Peng, J Zeng - Journal of Biomedical Informatics, 2022 - Elsevier
The goal of mortality prediction task is to predict the future death risk of patients according to
their previous Electronic Healthcare Records (EHR). The main challenge of mortality …

[HTML][HTML] Dynamic estimation of the probability of patient readmission to the ICU using electronic medical records

K Caballero, R Akella - AMIA Annual Symposium Proceedings, 2015 - ncbi.nlm.nih.gov
In this paper, we propose a framework to dynamically estimate the probability that a patient
is readmitted after he is discharged from the ICU and transferred to a lower level care. We …

Predicting patient readmission risk from medical text via knowledge graph enhanced multiview graph convolution

Q Lu, TH Nguyen, D Dou - Proceedings of the 44th international acm …, 2021 - dl.acm.org
Unplanned intensive care unit (ICU) readmission rate is an important metric for evaluating
the quality of hospital care. Efficient and accurate prediction of ICU readmission risk can not …

[HTML][HTML] Learning latent space representations to predict patient outcomes: Model development and validation

S Rongali, AJ Rose, DD McManus… - Journal of Medical …, 2020 - jmir.org
Background Scalable and accurate health outcome prediction using electronic health record
(EHR) data has gained much attention in research recently. Previous machine learning …

[HTML][HTML] Augmented intelligence facilitates concept mapping across different electronic health records

TA Dam, LM Fleuren, LF Roggeveen, M Otten… - International journal of …, 2023 - Elsevier
Introduction With the advent of artificial intelligence, the secondary use of routinely collected
medical data from electronic healthcare records (EHR) has become increasingly popular …

Discriminative features generation for mortality prediction in icu

S Pokharel, Z Shi, G Zuccon, Y Li - International Conference on Advanced …, 2020 - Springer
Effective methods for mortality prediction for Intensive Care Unit (ICU) patients assist health
professionals by producing alerts ahead of time regarding the critical changing …

Contrastive Learning-Based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling Using EHRs

Y Liu, Z Zhang, S Qin, FD Salim, AJ Yepes - Joint European Conference …, 2023 - Springer
Predicting the risk of in-hospital mortality from electronic health records (EHRs) has received
considerable attention. Such predictions will provide early warning of a patient's health …