Posts Tagged ‘time series’
Distinguishing neonatal culture-negative sepsis from rule-out sepsis with artificial intelligence-derived graphs.
Link: https://doi.org/10.1038/s41390-024-03458-z Authors: Holmes, Emma; Kauffman, Justin; Juliano, Courtney; Duchon, Jennifer; Nadkarni, Girish N Abstract: Novel artificial intelligence methods can aide in identification of cases of conditions using only unstructured electronic health record data. This graph-based method compares comprehensive electronic health records among neonates using temporal data. This provides a scalable solution to distinguish culture…
Read MoreA novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19.
Link: https://doi.org/S0933-3657(23)00264-6 Authors: Oh, Wonsuk; Jayaraman, Pushkala; Tandon, Pranai; Chaddha, Udit S; Kovatch, Patricia; Charney, Alexander W; Glicksberg, Benjamin S; Nadkarni, Girish N Abstract: Computational subphenotyping, a data-driven approach to understanding disease subtypes, is a prominent topic in medical research. Numerous ongoing studies are dedicated to developing advanced computational subphenotyping methods for cross-sectional data. However,…
Read MoreInteratrial Block Association With Adverse Cardiovascular Outcomes in Patients Without a History of Atrial Fibrillation.
Link: https://doi.org/S2405-500X(23)00254-2 Authors: Lampert, Joshua; Power, David; Havaldar, Shreyas; Govindarajulu, Usha; Kawamura, Iwanari; Maan, Abhishek; Miller, Marc A; Menon, Kartikeya; Koruth, Jacob; Whang, William; Bagiella, Emilia; Bayes-Genis, Antoni; Musikantow, Daniel; Turagam, Mohit; Bayes de Luna, Antoni; Halperin, Jonathan; Dukkipati, Srinivas R; Vaid, Akhil; Nadkarni, Girish; Glicksberg, Benjamin; Fuster, Valentin; Reddy, Vivek Y Abstract: Interatrial block…
Read MoreUsing sequence clustering to identify clinically relevant subphenotypes in patients with COVID-19 admitted to the intensive care unit.
Link: https://doi.org/10.1093/jamia/ocab252 Authors: Oh, Wonsuk; Jayaraman, Pushkala; Sawant, Ashwin S; Chan, Lili; Levin, Matthew A; Charney, Alexander W; Kovatch, Patricia; Glicksberg, Benjamin S; Nadkarni, Girish N Abstract: The novel coronavirus disease 2019 (COVID-19) has heterogenous clinical courses, indicating that there might be distinct subphenotypes in critically ill patients. Although prior research has identified these subphenotypes,…
Read MoreVisual Analytics to Leverage Anesthesia Electronic Health Record.
Link: https://doi.org/10.1213/ANE.0000000000006175 Authors: Kahn, Ronald A; Gal, Jonathan S; Hofer, Ira S; Wax, David B; Villar, Joshua I; Levin, Mathew A Abstract: Visual analytics is the science of analytical reasoning supported by interactive visual interfaces called dashboards. In this report, we describe our experience addressing the challenges in visual analytics of anesthesia electronic health record…
Read MoreAcute Kidney Injury in Patients Hospitalized With COVID-19 in New York City: Temporal Trends From March 2020 to April 2021.
Link: https://doi.org/10.1016/j.xkme.2021.06.008 Authors: Dellepiane, Sergio; Vaid, Akhil; Jaladanki, Suraj K; Coca, Steven; Fayad, Zahi A; Charney, Alexander W; Bottinger, Erwin P; He, John Cijiang; Glicksberg, Benjamin S; Chan, Lili; Nadkarni, Girish Abstract:
Read MoreImpact of institutional routine surveillance endomyocardial biopsy frequency in the first year on rejection and graft survival in pediatric heart transplantation.
Link: https://doi.org/10.1111/petr.14035 Authors: Duong, Son Q; Zhang, Yulin; Hall, Matt; Hollander, Seth A; Thurm, Cary W; Bernstein, Daniel; Feingold, Brian; Godown, Justin; Almond, Christopher Abstract: Routine surveillance biopsy (RSB) is performed to detect asymptomatic acute rejection (AR) after heart transplantation (HT). Variation in pediatric RSB across institutions is high. We examined center-based variation in RSB…
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