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 *

174 related articles for article (PubMed ID: 35511882)

  • 21. Mortality prediction in intensive care units with the Super ICU Learner Algorithm (SICULA): a population-based study.
    Pirracchio R; Petersen ML; Carone M; Rigon MR; Chevret S; van der Laan MJ
    Lancet Respir Med; 2015 Jan; 3(1):42-52. PubMed ID: 25466337
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A Novel Composite Indicator of Predicting Mortality Risk for Heart Failure Patients With Diabetes Admitted to Intensive Care Unit Based on Machine Learning.
    Yang B; Zhu Y; Lu X; Shen C
    Front Endocrinol (Lausanne); 2022; 13():917838. PubMed ID: 35846312
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU.
    Kong G; Lin K; Hu Y
    BMC Med Inform Decis Mak; 2020 Oct; 20(1):251. PubMed ID: 33008381
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study.
    Oh SS; Kuang I; Jeong H; Song JY; Ren B; Moon JY; Park EC; Kawachi I
    J Med Internet Res; 2023 Jul; 25():e45041. PubMed ID: 37463016
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Interpretable machine learning for predicting 28-day all-cause in-hospital mortality for hypertensive ischemic or hemorrhagic stroke patients in the ICU: a multi-center retrospective cohort study with internal and external cross-validation.
    Huang J; Chen H; Deng J; Liu X; Shu T; Yin C; Duan M; Fu L; Wang K; Zeng S
    Front Neurol; 2023; 14():1185447. PubMed ID: 37614971
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm.
    Ren W; Zou K; Huang S; Xu H; Zhang W; Shi X; Shi L; Zhong X; Peng Y; Tang X; Lü M
    J Clin Gastroenterol; 2024 Jul; 58(6):619-626. PubMed ID: 37712768
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Predicting Discharge Destination of Critically Ill Patients Using Machine Learning.
    Abad ZSH; Maslove DM; Lee J
    IEEE J Biomed Health Inform; 2021 Mar; 25(3):827-837. PubMed ID: 32750906
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study.
    Hur S; Min JY; Yoo J; Kim K; Chung CR; Dykes PC; Cha WC
    J Med Internet Res; 2021 Aug; 23(8):e23508. PubMed ID: 34382940
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Machine learning prediction models and nomogram to predict the risk of in-hospital death for severe DKA: A clinical study based on MIMIC-IV, eICU databases, and a college hospital ICU.
    Xie W; Li Y; Meng X; Zhao M
    Int J Med Inform; 2023 Jun; 174():105049. PubMed ID: 37001474
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Novel pneumonia score based on a machine learning model for predicting mortality in pneumonia patients on admission to the intensive care unit.
    Wang B; Li Y; Tian Y; Ju C; Xu X; Pei S
    Respir Med; 2023 Oct; 217():107363. PubMed ID: 37451647
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study.
    Nanayakkara S; Fogarty S; Tremeer M; Ross K; Richards B; Bergmeir C; Xu S; Stub D; Smith K; Tacey M; Liew D; Pilcher D; Kaye DM
    PLoS Med; 2018 Nov; 15(11):e1002709. PubMed ID: 30500816
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A time-incorporated SOFA score-based machine learning model for predicting mortality in critically ill patients: A multicenter, real-world study.
    Liu Y; Gao K; Deng H; Ling T; Lin J; Yu X; Bo X; Zhou J; Gao L; Wang P; Hu J; Zhang J; Tong Z; Liu Y; Shi Y; Ke L; Gao Y; Li W
    Int J Med Inform; 2022 Jul; 163():104776. PubMed ID: 35512625
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Development of a machine learning-based prediction model for sepsis-associated delirium in the intensive care unit.
    Zhang Y; Hu J; Hua T; Zhang J; Zhang Z; Yang M
    Sci Rep; 2023 Aug; 13(1):12697. PubMed ID: 37542106
    [TBL] [Abstract][Full Text] [Related]  

  • 34. [Predicting prolonged length of intensive care unit stay
    Wu JY; Lin Y; Lin K; Hu YH; Kong GL
    Beijing Da Xue Xue Bao Yi Xue Ban; 2021 Dec; 53(6):1163-1170. PubMed ID: 34916699
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Integrating Structured and Unstructured EHR Data for Predicting Mortality by Machine Learning and Latent Dirichlet Allocation Method.
    Chiu CC; Wu CM; Chien TN; Kao LJ; Li C; Chu CM
    Int J Environ Res Public Health; 2023 Feb; 20(5):. PubMed ID: 36901354
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Explainable Machine-Learning Model for Prediction of In-Hospital Mortality in Septic Patients Requiring Intensive Care Unit Readmission.
    Hu C; Li L; Li Y; Wang F; Hu B; Peng Z
    Infect Dis Ther; 2022 Aug; 11(4):1695-1713. PubMed ID: 35835943
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.
    Zhao QY; Wang H; Luo JC; Luo MH; Liu LP; Yu SJ; Liu K; Zhang YJ; Sun P; Tu GW; Luo Z
    Front Med (Lausanne); 2021; 8():676343. PubMed ID: 34079812
    [No Abstract]   [Full Text] [Related]  

  • 38. Machine learning-based in-hospital mortality risk prediction tool for intensive care unit patients with heart failure.
    Chen Z; Li T; Guo S; Zeng D; Wang K
    Front Cardiovasc Med; 2023; 10():1119699. PubMed ID: 37077747
    [TBL] [Abstract][Full Text] [Related]  

  • 39. SEVERITAS: An externally validated mortality prediction for critically ill patients in low and middle-income countries.
    Deliberato RO; Escudero GG; Bulgarelli L; Neto AS; Ko SQ; Campos NS; Saat B; Amaro E; Lopes FS; Johnson AE
    Int J Med Inform; 2019 Nov; 131():103959. PubMed ID: 31539837
    [TBL] [Abstract][Full Text] [Related]  

  • 40.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

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