Gilles Clermont
Affiliations: | Critical Care Medicine | University of Pittsburgh, Pittsburgh, PA, United States |
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"Gilles Clermont"
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| Chen Y, Yoon JH, Pinsky MR, et al. (2020) Development of hemorrhage identification model using non-invasive vital signs. Physiological Measurement |
| Yoon JH, Mu L, Chen L, et al. (2019) Predicting tachycardia as a surrogate for instability in the intensive care unit. Journal of Clinical Monitoring and Computing |
| De-Arteaga M, Chen J, Huggins P, et al. (2019) Predicting neurological recovery with Canonical Autocorrelation Embeddings. Plos One. 14: e0210966 |
| Murugan R, Balakumar V, Kerti SJ, et al. (2018) Net ultrafiltration intensity and mortality in critically ill patients with fluid overload. Critical Care (London, England). 22: 223 |
| Ramirez-Zuniga I, Rubin JE, Swigon D, et al. (2018) Mathematical Modeling of Energy Consumption in the Acute Inflammatory Response. Journal of Theoretical Biology |
| Seymour CW, Gomez H, Chang CH, et al. (2017) Precision medicine for all? Challenges and opportunities for a precision medicine approach to critical illness. Critical Care (London, England). 21: 257 |
| Jin K, Murugan R, Sileanu FE, et al. (2017) Intensive Monitoring of Urine Output is Associated with Increased Detection of Acute Kidney Injury and Improved Outcomes. Chest |
| Richards E, Clermont G, Parker RS. (2017) Modeling Fluid Volume and Creatinine Dynamics during Acute Kidney Injury and Edema Ifac-Papersonline. 50: 6678-6683 |
| Hauskrecht M, Batal I, Hong C, et al. (2016) Outlier-based detection of unusual patient-management actions: an ICU study. Journal of Biomedical Informatics |
| Zhang LA, Parker RS, Swigon D, et al. (2016) A One-Nearest-Neighbor Approach to Identify the Original Time of Infection Using Censored Baboon Sepsis Data. Critical Care Medicine |