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Cited by in CrossRef
For: Dhungana P, Serafim LP, Ruiz AL, Bruns D, Weister TJ, Smischney NJ, Kashyap R. Machine learning in data abstraction: A computable phenotype for sepsis and septic shock diagnosis in the intensive care unit. World J Crit Care Med 2019; 8(7): 120-126 [PMID: 31853447 DOI: 10.5492/wjccm.v8.i7.120]
URL: https://www.wjgnet.com/2220-3141/full/v8/i7/120.htm
Number Citing Articles
1
Fudan Zheng, Luhao Wang, Yuxian Pang, Zhiguang Chen, Yutong Lu, Yuedong Yang, Jianfeng Wu. ShockSurv: A machine learning model to accurately predict 28-day mortality for septic shock patients in the intensive care unitBiomedical Signal Processing and Control 2023; 86: 105146 doi: 10.1016/j.bspc.2023.105146
2
Erin F. Barreto, Jack Chang, Andrew D. Rule, Kristin C. Mara, Laurie A. Meade, Johar Paul, Paul J. Jannetto, Arjun P. Athreya, Marc H. Scheetz, James E. Leggett. Population pharmacokinetic model of cefepime for critically ill adults: a comparative assessment of eGFR equationsAntimicrobial Agents and Chemotherapy 2023; 67(11) doi: 10.1128/aac.00810-23
3
Daniele Roberto Giacobbe, Alessio Signori, Filippo Del Puente, Sara Mora, Luca Carmisciano, Federica Briano, Antonio Vena, Lorenzo Ball, Chiara Robba, Paolo Pelosi, Mauro Giacomini, Matteo Bassetti. Early Detection of Sepsis With Machine Learning Techniques: A Brief Clinical PerspectiveFrontiers in Medicine 2021; 8 doi: 10.3389/fmed.2021.617486
4
Xuan Song, Timothy J. Weister, Yue Dong, Kianoush B. Kashani, Rahul Kashyap. Derivation and Validation of an Automated Search Strategy to Retrospectively Identify Acute Respiratory Distress Patients Per Berlin DefinitionFrontiers in Medicine 2021; 8 doi: 10.3389/fmed.2021.614380
5
Svetlana Herasevich, Phillip J. Schulte, William J. Hogan, Hassan Alkhateeb, Zhenmei Zhang, Bradley A. White, Nandita Khera, Vivek Roy, Ognjen Gajic, Hemang Yadav. Lung Injury Prediction Model in Bone Marrow Transplantation: A Multicenter Cohort StudyAmerican Journal of Respiratory and Critical Care Medicine 2024; 209(5): 543 doi: 10.1164/rccm.202308-1524OC
6
Nianzong Hou, Mingzhe Li, Lu He, Bing Xie, Lin Wang, Rumin Zhang, Yong Yu, Xiaodong Sun, Zhengsheng Pan, Kai Wang. Predicting 30-days mortality for MIMIC-III patients with sepsis-3: a machine learning approach using XGboostJournal of Translational Medicine 2020; 18(1) doi: 10.1186/s12967-020-02620-5
7
Yonghua Fan, Qiufeng Han, Jinfeng Li, Gaige Ye, Xianjing Zhang, Tengxiao Xu, Huaqing Li. Revealing potential diagnostic gene biomarkers of septic shock based on machine learning analysisBMC Infectious Diseases 2022; 22(1) doi: 10.1186/s12879-022-07056-4
8
Franz-Simon Centner, Mariella Eliana Oster, Franz-Joseph Dally, Johannes Sauter-Servaes, Tanja Pelzer, Jochen Johannes Schoettler, Bianka Hahn, Anna-Meagan Fairley, Amr Abdulazim, Katharina Antonia Margarete Hackenberg, Christoph Groden, Nima Etminan, Joerg Krebs, Manfred Thiel, Holger Wenz, Máté Elod Maros. Comparative Analyses of the Impact of Different Criteria for Sepsis Diagnosis on Outcome in Patients with Spontaneous Subarachnoid HemorrhageJournal of Clinical Medicine 2022; 11(13): 3873 doi: 10.3390/jcm11133873
9
Smitesh Padte, Vikramaditya Samala Venkata, Priyal Mehta, Sawsan Tawfeeq, Rahul Kashyap, Salim Surani. 21st century critical care medicine: An overviewWorld Journal of Critical Care Medicine 2024; 13(1): 90176 doi: 10.5492/wjccm.v13.i1.90176
10
Heyi Li, Yewande E. Odeyemi, Timothy J. Weister, Chang Liu, Sarah J. Chalmers, Amos Lal, Xuan Song, Ognjen Gajic, Rahul Kashyap. Rule-Based Cohort Definitions for Acute Respiratory Distress Syndrome: A Computable Phenotyping Strategy Based on the Berlin DefinitionCritical Care Explorations 2021; 3(6): e0451 doi: 10.1097/CCE.0000000000000451
11
Tabinda Jawaid, Naseema Gangat, Timothy Weister, Rahul Kashyap. An Electronic Search Algorithm for Early Disseminated Intravascular Coagulopathy Diagnosis in the Intensive Care Unit: A Derivation and Validation StudyCureus 2020;  doi: 10.7759/cureus.10972