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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

166 related articles for article (PubMed ID: 35176113)

  • 21. Predicting hospital admissions at emergency department triage using routine administrative data.
    Sun Y; Heng BH; Tay SY; Seow E
    Acad Emerg Med; 2011 Aug; 18(8):844-50. PubMed ID: 21843220
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units.
    Fenn A; Davis C; Buckland DM; Kapadia N; Nichols M; Gao M; Knechtle W; Balu S; Sendak M; Theiling BJ
    Ann Emerg Med; 2021 Aug; 78(2):290-302. PubMed ID: 33972128
    [TBL] [Abstract][Full Text] [Related]  

  • 23. 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]  

  • 24. Triage Performance in Emergency Medicine: A Systematic Review.
    Hinson JS; Martinez DA; Cabral S; George K; Whalen M; Hansoti B; Levin S
    Ann Emerg Med; 2019 Jul; 74(1):140-152. PubMed ID: 30470513
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. Predicting hospital admission at the emergency department triage: A novel prediction model.
    Parker CA; Liu N; Wu SX; Shen Y; Lam SSW; Ong MEH
    Am J Emerg Med; 2019 Aug; 37(8):1498-1504. PubMed ID: 30413365
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Machine learning-based triage to identify low-severity patients with a short discharge length of stay in emergency department.
    Chang YH; Shih HM; Wu JE; Huang FW; Chen WK; Chen DM; Chung YT; Wang CCN
    BMC Emerg Med; 2022 May; 22(1):88. PubMed ID: 35596154
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions.
    Xie F; Ong MEH; Liew JNMH; Tan KBK; Ho AFW; Nadarajan GD; Low LL; Kwan YH; Goldstein BA; Matchar DB; Chakraborty B; Liu N
    JAMA Netw Open; 2021 Aug; 4(8):e2118467. PubMed ID: 34448870
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Machine learning models predicting undertriage in telephone triage.
    Inokuchi R; Iwagami M; Sun Y; Sakamoto A; Tamiya N
    Ann Med; 2022 Dec; 54(1):2990-2997. PubMed ID: 36286496
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Deep Learning Algorithm to Predict Need for Critical Care in Pediatric Emergency Departments.
    Kwon JM; Jeon KH; Lee M; Kim KH; Park J; Oh BH
    Pediatr Emerg Care; 2021 Dec; 37(12):e988-e994. PubMed ID: 31268962
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Development and validation of a machine learning framework for improved resource allocation in the emergency department.
    El Ariss AB; Kijpaisalratana N; Ahmed S; Yuan J; Coleska A; Marshall A; Luo AD; He S
    Am J Emerg Med; 2024 Oct; 84():141-148. PubMed ID: 39127019
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index.
    Levin S; Toerper M; Hamrock E; Hinson JS; Barnes S; Gardner H; Dugas A; Linton B; Kirsch T; Kelen G
    Ann Emerg Med; 2018 May; 71(5):565-574.e2. PubMed ID: 28888332
    [TBL] [Abstract][Full Text] [Related]  

  • 33. 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]  

  • 34. Risk of mortality and cardiopulmonary arrest in critical patients presenting to the emergency department using machine learning and natural language processing.
    Fernandes M; Mendes R; Vieira SM; Leite F; Palos C; Johnson A; Finkelstein S; Horng S; Celi LA
    PLoS One; 2020; 15(4):e0230876. PubMed ID: 32240233
    [TBL] [Abstract][Full Text] [Related]  

  • 35. 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]  

  • 36. Comparing resource use between paediatric emergency department visits by triage level.
    Samuels-Kalow ME; Niedzwiecki M; Friedman AB; Sokolove PE; Hsia RY
    Emerg Med J; 2018 Nov; 35(11):681-684. PubMed ID: 30181161
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Emergency department children are not as sick as adults: implications for critical care skills retention in an exclusively pediatric emergency medicine practice.
    Green SM; Ruben J
    J Emerg Med; 2009 Nov; 37(4):359-68. PubMed ID: 18022780
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Soft tissue oxygen saturation to predict admission from the emergency department: A prospective observational study.
    Davis WT; Lospinso J; Barnwell RM; Hughes J; Schauer SG; Smith TB; April MD
    Am J Emerg Med; 2017 Aug; 35(8):1111-1117. PubMed ID: 28343815
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Can paediatric early warning scores (PEWS) be used to guide the need for hospital admission and predict significant illness in children presenting to the emergency department? An assessment of PEWS diagnostic accuracy using sensitivity and specificity.
    Lillitos PJ; Hadley G; Maconochie I
    Emerg Med J; 2016 May; 33(5):329-37. PubMed ID: 26531861
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Machine Learning-Based Prediction of Korean Triage and Acuity Scale Level in Emergency Department Patients.
    Choi SW; Ko T; Hong KJ; Kim KH
    Healthc Inform Res; 2019 Oct; 25(4):305-312. PubMed ID: 31777674
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.