These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
2. Emergency department triage prediction of clinical outcomes using machine learning models. Raita Y; Goto T; Faridi MK; Brown DFM; Camargo CA; Hasegawa K Crit Care; 2019 Feb; 23(1):64. PubMed ID: 30795786 [TBL] [Abstract][Full Text] [Related]
3. Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage. Goto T; Camargo CA; Faridi MK; Freishtat RJ; Hasegawa K JAMA Netw Open; 2019 Jan; 2(1):e186937. PubMed ID: 30646206 [TBL] [Abstract][Full Text] [Related]
4. Emergency department disposition prediction using a deep neural network with integrated clinical narratives and structured data. Chen CH; Hsieh JG; Cheng SL; Lin YL; Lin PH; Jeng JH Int J Med Inform; 2020 Jul; 139():104146. PubMed ID: 32387818 [TBL] [Abstract][Full Text] [Related]
5. Advancing Emergency Department Triage Prediction With Machine Learning to Optimize Triage for Abdominal Pain Surgery Patients. Chai C; Peng SZ; Zhang R; Li CW; Zhao Y Surg Innov; 2024 Dec; 31(6):583-597. PubMed ID: 39150388 [TBL] [Abstract][Full Text] [Related]
6. Patient stratification based on the risk of severe illness in emergency departments through collaborative machine learning models. Chen JY; Hsieh CC; Lee JT; Lin CH; Kao CY Am J Emerg Med; 2024 Aug; 82():142-152. PubMed ID: 38908339 [TBL] [Abstract][Full Text] [Related]
7. A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study. Yao LH; Leung KC; Tsai CL; Huang CH; Fu LC J Med Internet Res; 2021 Dec; 23(12):e27008. PubMed ID: 34958305 [TBL] [Abstract][Full Text] [Related]
8. Developing machine learning models to personalize care levels among emergency room patients for hospital admission. Nguyen M; Corbin CK; Eulalio T; Ostberg NP; Machiraju G; Marafino BJ; Baiocchi M; Rose C; Chen JH J Am Med Inform Assoc; 2021 Oct; 28(11):2423-2432. PubMed ID: 34402507 [TBL] [Abstract][Full Text] [Related]
9. Machine learning algorithms for early sepsis detection in the emergency department: A retrospective study. Kijpaisalratana N; Sanglertsinlapachai D; Techaratsami S; Musikatavorn K; Saoraya J Int J Med Inform; 2022 Apr; 160():104689. PubMed ID: 35078027 [TBL] [Abstract][Full Text] [Related]
10. Predicting adult neuroscience intensive care unit admission from emergency department triage using a retrospective, tabular-free text machine learning approach. Klang E; Kummer BR; Dangayach NS; Zhong A; Kia MA; Timsina P; Cossentino I; Costa AB; Levin MA; Oermann EK Sci Rep; 2021 Jan; 11(1):1381. PubMed ID: 33446890 [TBL] [Abstract][Full Text] [Related]
11. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach. Taylor RA; Pare JR; Venkatesh AK; Mowafi H; Melnick ER; Fleischman W; Hall MK Acad Emerg Med; 2016 Mar; 23(3):269-78. PubMed ID: 26679719 [TBL] [Abstract][Full Text] [Related]
12. Machine learning for developing a prediction model of hospital admission of emergency department patients: Hype or hope? De Hond A; Raven W; Schinkelshoek L; Gaakeer M; Ter Avest E; Sir O; Lameijer H; Hessels RA; Reijnen R; De Jonge E; Steyerberg E; Nickel CH; De Groot B Int J Med Inform; 2021 Aug; 152():104496. PubMed ID: 34020171 [TBL] [Abstract][Full Text] [Related]
13. Machine learning approaches for predicting disposition of asthma and COPD exacerbations in the ED. Goto T; Camargo CA; Faridi MK; Yun BJ; Hasegawa K Am J Emerg Med; 2018 Sep; 36(9):1650-1654. PubMed ID: 29970272 [TBL] [Abstract][Full Text] [Related]
14. Criticality and clinical department prediction of ED patients using machine learning based on heterogeneous medical data. Xiao Y; Zhang J; Chi C; Ma Y; Song A Comput Biol Med; 2023 Oct; 165():107390. PubMed ID: 37659113 [TBL] [Abstract][Full Text] [Related]
15. An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study. Lee S; Kang WS; Kim DW; Seo SH; Kim J; Jeong ST; Yon DK; Lee J J Med Internet Res; 2023 Aug; 25():e49283. PubMed ID: 37642984 [TBL] [Abstract][Full Text] [Related]
16. Validation of deep-learning-based triage and acuity score using a large national dataset. Kwon JM; Lee Y; Lee Y; Lee S; Park H; Park J PLoS One; 2018; 13(10):e0205836. PubMed ID: 30321231 [TBL] [Abstract][Full Text] [Related]
17. Machine learning-based prediction of critical illness in children visiting the emergency department. Hwang S; Lee B PLoS One; 2022; 17(2):e0264184. PubMed ID: 35176113 [TBL] [Abstract][Full Text] [Related]
18. Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques. Saggu S; Daneshvar H; Samavi R; Pires P; Sassi RB; Doyle TE; Zhao J; Mauluddin A; Duncan L BMC Med Inform Decis Mak; 2024 Feb; 24(1):42. PubMed ID: 38331816 [TBL] [Abstract][Full Text] [Related]
19. Predicting in-hospital mortality in adult non-traumatic emergency department patients: a retrospective comparison of the Modified Early Warning Score (MEWS) and machine learning approach. Wu KH; Cheng FJ; Tai HL; Wang JC; Huang YT; Su CM; Chang YN PeerJ; 2021; 9():e11988. PubMed ID: 34513328 [TBL] [Abstract][Full Text] [Related]
20. Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks. Zhang X; Kim J; Patzer RE; Pitts SR; Patzer A; Schrager JD Methods Inf Med; 2017 Oct; 56(5):377-389. PubMed ID: 28816338 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]