Predicting Patient's Trajectory of Physiological Data using Temporal Trends in Similar Patients: A System for Near-Term Prognostics.
By Shahram Ebadollahi, Jimeng Sun, David Gotz, Jianying Hu, Daby M. Sow, Chalapathy Neti. 2010
87 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Yejin Kim
- Xiaoqian Jiang
- Hwanjo Yu
- Jimeng Sun
- Charu C. Aggarwal
- Payman Mohassel
- Jing Ma
- Charalampos E. Tsourakakis
Citations in the corpus
- Federated Tensor Factorization for Computational Phenotyping (2017, background): “Electronic health records (EHRs) become one of most important sources of information about patients, which provide insight into diagnoses [19] and prognoses [11], as well as assist in the development of cost-eective treatment andmanagement programs [1, 12].”
- L G ] 1 1 A pr 2 01 7 Federated Tensor Factorization for Computational Phenotyping (2018, background): “Electronic health records (EHRs) become one of most important sources of information about patients, which provide insight into diagnoses [19] and prognoses [11], as well as assist in the development of cost-effective treatment andmanagement programs [1, 12].”