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 *

383 related articles for article (PubMed ID: 35033770)

  • 1. Machine learning-based in-hospital mortality prediction models for patients with acute coronary syndrome.
    Ke J; Chen Y; Wang X; Wu Z; Zhang Q; Lian Y; Chen F
    Am J Emerg Med; 2022 Mar; 53():127-134. PubMed ID: 35033770
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The prediction of in-hospital mortality in chronic kidney disease patients with coronary artery disease using machine learning models.
    Ye Z; An S; Gao Y; Xie E; Zhao X; Guo Z; Li Y; Shen N; Ren J; Zheng J
    Eur J Med Res; 2023 Jan; 28(1):33. PubMed ID: 36653875
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Predicting in-hospital mortality in ICU patients with sepsis using gradient boosting decision tree.
    Li K; Shi Q; Liu S; Xie Y; Liu J
    Medicine (Baltimore); 2021 May; 100(19):e25813. PubMed ID: 34106618
    [TBL] [Abstract][Full Text] [Related]  

  • 4. In-hospital mortality risk stratification of Asian ACS patients with artificial intelligence algorithm.
    Kasim S; Malek S; Song C; Wan Ahmad WA; Fong A; Ibrahim KS; Safiruz MS; Aziz F; Hiew JH; Ibrahim N
    PLoS One; 2022; 17(12):e0278944. PubMed ID: 36508425
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sensitive troponin assays and N-terminal pro-B-type natriuretic peptide in acute coronary syndrome: prediction of significant coronary lesions and long-term prognosis.
    Gravning J; Smedsrud MK; Omland T; Eek C; Skulstad H; Aaberge L; Bendz B; Kjekshus J; Mørkrid L; Edvardsen T
    Am Heart J; 2013 May; 165(5):716-24. PubMed ID: 23622908
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Machine learning for early prediction of in-hospital cardiac arrest in patients with acute coronary syndromes.
    Wu TT; Lin XQ; Mu Y; Li H; Guo YS
    Clin Cardiol; 2021 Mar; 44(3):349-356. PubMed ID: 33586214
    [TBL] [Abstract][Full Text] [Related]  

  • 8. NT-proBNP for prognostic and diagnostic evaluation in patients with acute coronary syndromes.
    Zdravkovic V; Mladenovic V; Colic M; Bankovic D; Lazic Z; Petrovic M; Simic I; Knezevic S; Pantovic S; Djukic A; Zdravkovic N
    Kardiol Pol; 2013; 71(5):472-9. PubMed ID: 23788087
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Construction of a Risk Prediction Model for Hospital-Acquired Pulmonary Embolism in Hospitalized Patients.
    Hou L; Hu L; Gao W; Sheng W; Hao Z; Chen Y; Li J
    Clin Appl Thromb Hemost; 2021; 27():10760296211040868. PubMed ID: 34558325
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predictive value of N-terminal pro-B-type natriuretic peptide (NT-pro BNP) combined with D-dimer for no-reflow phenomenon in patients with acute coronary syndrome after emergency of percutaneous coronary intervention.
    Diao Y; Yin M; Zhang B; Sun B
    Bioengineered; 2021 Dec; 12(1):8614-8621. PubMed ID: 34612772
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction of clinical outcome in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) using the TIMI risk score extended by N-terminal pro-brain natriuretic peptide levels.
    Jarai R; Iordanova N; Jarai R; Jarai F; Raffetseder A; Woloszczuk W; Gyöngyösi M; Geyer G; Wojta J; Huber K
    Wien Klin Wochenschr; 2007; 119(21-22):626-32. PubMed ID: 18043882
    [TBL] [Abstract][Full Text] [Related]  

  • 12. N-terminal B-type natriuretic peptide assessment provides incremental prognostic information in patients with acute coronary syndromes and normal troponin T values upon admission.
    Weber M; Bazzino O; Navarro Estrada JL; Fuselli JJ; Botto F; Perez de Arenaza D; Möllmann H; Nef HN; Elsässer A; Hamm CW
    J Am Coll Cardiol; 2008 Mar; 51(12):1188-95. PubMed ID: 18355657
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Diagnosis of Acute Coronary Syndrome with a Support Vector Machine.
    Berikol GB; Yildiz O; Özcan IT
    J Med Syst; 2016 Apr; 40(4):84. PubMed ID: 26815338
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning in the prediction of in-hospital mortality in patients with first acute myocardial infarction.
    Zhu X; Xie B; Chen Y; Zeng H; Hu J
    Clin Chim Acta; 2024 Feb; 554():117776. PubMed ID: 38216028
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predictive value of NT-proBNP for 30-day mortality in patients with non-ST-elevation acute coronary syndromes: a comparison with the GRACE and TIMI risk scores.
    Schellings DA; Adiyaman A; Dambrink JE; Gosselink AM; Kedhi E; Roolvink V; Ottervanger JP; Van't Hof AW
    Vasc Health Risk Manag; 2016; 12():471-476. PubMed ID: 27920547
    [TBL] [Abstract][Full Text] [Related]  

  • 16. [Age-related differences in the management and outcome of acute coronary syndrome under the chest pain center model: a multicenter retrospective study].
    Li S; Ding X; Ye T; Cheng L; Cui C; Zhang Y; Zhu F; Jiang X; Cai L
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2021 Mar; 33(3):318-323. PubMed ID: 33834973
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Use of machine learning models to predict in-hospital mortality in patients with acute coronary syndrome.
    Li R; Shen L; Ma W; Yan B; Chen W; Zhu J; Li L; Yuan J; Pan C
    Clin Cardiol; 2023 Feb; 46(2):184-194. PubMed ID: 36479714
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Novel scoring system based on clinical examination for prediction of in-hospital mortality in acute coronary syndrome patients: a retrospective cohort study.
    Pramudyo M; Bijaksana TL; Yahya AF; Putra ICS
    Open Heart; 2022 Oct; 9(2):. PubMed ID: 36229139
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Extensive phenotype data and machine learning in prediction of mortality in acute coronary syndrome - the MADDEC study.
    Hernesniemi JA; Mahdiani S; Tynkkynen JA; Lyytikäinen LP; Mishra PP; Lehtimäki T; Eskola M; Nikus K; Antila K; Oksala N
    Ann Med; 2019 Mar; 51(2):156-163. PubMed ID: 31030570
    [No Abstract]   [Full Text] [Related]  

  • 20. Artificial intelligence based prediction model of in-hospital mortality among females with acute coronary syndrome: for the Jerusalem Platelets Thrombosis and Intervention in Cardiology (JUPITER-12) Study Group.
    Loutati R; Perel N; Marmor D; Maller T; Taha L; Amsalem I; Hitter R; Mohammed M; Levi N; Shrem M; Amro M; Shuvy M; Glikson M; Asher E
    Front Cardiovasc Med; 2024; 11():1333252. PubMed ID: 38500758
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 20.