BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

116 related articles for article (PubMed ID: 34001314)

  • 1. Survival in the Intensive Care Unit: A prognosis model based on Bayesian classifiers.
    Delgado R; Núñez-González JD; Yébenes JC; Lavado Á
    Artif Intell Med; 2021 May; 115():102054. PubMed ID: 34001314
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.
    Awad A; Bader-El-Den M; McNicholas J; Briggs J
    Int J Med Inform; 2017 Dec; 108():185-195. PubMed ID: 29132626
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of mortality in Intensive Care Units: a multivariate feature selection.
    Monteiro F; Meloni F; Baranauskas JA; Macedo AA
    J Biomed Inform; 2020 Jul; 107():103456. PubMed ID: 32454242
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Acute Physiology and Chronic Health Evaluation II score for the assessment of mortality prediction in the intensive care unit: a single-centre study from Iran.
    Bahtouee M; Eghbali SS; Maleki N; Rastgou V; Motamed N
    Nurs Crit Care; 2019 Nov; 24(6):375-380. PubMed ID: 30924584
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluation of predictive ability of APACHE II system and hospital outcome in Canadian intensive care unit patients.
    Wong DT; Crofts SL; Gomez M; McGuire GP; Byrick RJ
    Crit Care Med; 1995 Jul; 23(7):1177-83. PubMed ID: 7600824
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Bayesian approach to predict hospital mortality of intensive care readmissions during the same hospitalisation.
    Ho KM; Knuiman M
    Anaesth Intensive Care; 2008 Jan; 36(1):38-45. PubMed ID: 18326130
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Early Prognostication of Critical Patients With Spinal Cord Injury: A Machine Learning Study With 1485 Cases.
    Fan G; Liu H; Yang S; Luo L; Pang M; Liu B; Zhang L; Han L; Rong L; Liao X
    Spine (Phila Pa 1976); 2024 Jun; 49(11):754-762. PubMed ID: 37921018
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Survival prediction in intensive-care units based on aggregation of long-term disease history and acute physiology: a retrospective study of the Danish National Patient Registry and electronic patient records.
    Nielsen AB; Thorsen-Meyer HC; Belling K; Nielsen AP; Thomas CE; Chmura PJ; Lademann M; Moseley PL; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Perner A; Brunak S
    Lancet Digit Health; 2019 Jun; 1(2):e78-e89. PubMed ID: 33323232
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Prediction of outcome from intensive care: a prospective cohort study comparing Acute Physiology and Chronic Health Evaluation II and III prognostic systems in a United Kingdom intensive care unit.
    Beck DH; Taylor BL; Millar B; Smith GB
    Crit Care Med; 1997 Jan; 25(1):9-15. PubMed ID: 8989170
    [TBL] [Abstract][Full Text] [Related]  

  • 10. [Value of serum cholinesterase in the prognosis of septic shock].
    Zhao R; Zhang X; Wang H; Zhang R; Duan X; Liu S; Han B; Ding X; Wang D; Sun T
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2020 Jan; 32(1):44-49. PubMed ID: 32148230
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.
    Thorsen-Meyer HC; Nielsen AB; Nielsen AP; Kaas-Hansen BS; Toft P; Schierbeck J; Strøm T; Chmura PJ; Heimann M; Dybdahl L; Spangsege L; Hulsen P; Belling K; Brunak S; Perner A
    Lancet Digit Health; 2020 Apr; 2(4):e179-e191. PubMed ID: 33328078
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The Pros and Cons of the Prediction Game: The Never-ending Debate of Mortality in the Intensive Care Unit.
    Fuchs PA; Czech IJ; Krzych ŁJ
    Int J Environ Res Public Health; 2019 Sep; 16(18):. PubMed ID: 31540201
    [TBL] [Abstract][Full Text] [Related]  

  • 13. [Combined prognostic value of serum lactic acid, procalcitonin and severity score for short-term prognosis of septic shock patients].
    Hao C; Hu Q; Zhu L; Xu H; Zhang Y
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2021 Mar; 33(3):281-285. PubMed ID: 33834968
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Cost-utility in medical intensive care patients. Rationalizing ongoing care and timing of discharge from intensive care.
    Thomas K; Peter JV; Christina J; Jagadish AR; Rajan A; Lionel P; Jeyaseelan L; Yadav B; John G; Pichamuthu K; Chacko B; Pari P; Murugesan T; Rajendran K; John A; Sathyendra S; Iyyadurai R; Jasmine S; Karthik R; Mathuram A; Hansdak SG; Abhilash KP; Kumar S; John KR; Sudarsanam TD
    Ann Am Thorac Soc; 2015 Jul; 12(7):1058-65. PubMed ID: 26011090
    [TBL] [Abstract][Full Text] [Related]  

  • 15. [Formulation of combined predictive indicators using logistic regression model in predicting sepsis and prognosis].
    Duan L; Zhang S; Lin Z
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2017 Feb; 29(2):139-144. PubMed ID: 28625261
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Performance evaluation of APACHE II score for an Indian patient with respiratory problems.
    Gupta R; Arora VK
    Indian J Med Res; 2004 Jun; 119(6):273-82. PubMed ID: 15243165
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Efficacy of the APACHE II score at ICU discharge in predicting post-ICU mortality and ICU readmission in critically ill surgical patients.
    Lee H; Lim CW; Hong HP; Ju JW; Jeon YT; Hwang JW; Park HP
    Anaesth Intensive Care; 2015 Mar; 43(2):175-86. PubMed ID: 25735682
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Intensive care unit prognostic scoring systems to predict death: a cost-effectiveness analysis.
    Glance LG; Osler T; Shinozaki T
    Crit Care Med; 1998 Nov; 26(11):1842-9. PubMed ID: 9824077
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mortality prediction in intensive care units (ICUs) using a deep rule-based fuzzy classifier.
    Davoodi R; Moradi MH
    J Biomed Inform; 2018 Mar; 79():48-59. PubMed ID: 29471111
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Use of Acute Physiology and Chronic Health Evaluation (APACHE)-II and Red Cell Distribution Width (RDW) for Assessment of Mortality of Patients with Sepsis in ICU.
    Huda AQ; Karim MR; Mahmud MA; Islam MS; Haque MF; Islam MR; Hossain MA
    Mymensingh Med J; 2017 Jul; 26(3):585-591. PubMed ID: 28919614
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.