BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

485 related articles for article (PubMed ID: 36711330)

  • 1. Twenty-eight-day in-hospital mortality prediction for elderly patients with ischemic stroke in the intensive care unit: Interpretable machine learning models.
    Huang J; Jin W; Duan X; Liu X; Shu T; Fu L; Deng J; Chen H; Liu G; Jiang Y; Liu Z
    Front Public Health; 2022; 10():1086339. PubMed ID: 36711330
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Interpretable machine learning model for early prediction of 28-day mortality in ICU patients with sepsis-induced coagulopathy: development and validation.
    Zhou S; Lu Z; Liu Y; Wang M; Zhou W; Cui X; Zhang J; Xiao W; Hua T; Zhu H; Yang M
    Eur J Med Res; 2024 Jan; 29(1):14. PubMed ID: 38172962
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Interpretable machine learning for 28-day all-cause in-hospital mortality prediction in critically ill patients with heart failure combined with hypertension: A retrospective cohort study based on medical information mart for intensive care database-IV and eICU databases.
    Peng S; Huang J; Liu X; Deng J; Sun C; Tang J; Chen H; Cao W; Wang W; Duan X; Luo X; Peng S
    Front Cardiovasc Med; 2022; 9():994359. PubMed ID: 36312291
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study.
    Li J; Liu S; Hu Y; Zhu L; Mao Y; Liu J
    J Med Internet Res; 2022 Aug; 24(8):e38082. PubMed ID: 35943767
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Machine learning for prediction of in-hospital mortality in lung cancer patients admitted to intensive care unit.
    Huang T; Le D; Yuan L; Xu S; Peng X
    PLoS One; 2023; 18(1):e0280606. PubMed ID: 36701342
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.
    Pan P; Li Y; Xiao Y; Han B; Su L; Su M; Li Y; Zhang S; Jiang D; Chen X; Zhou F; Ma L; Bao P; Xie L
    J Med Internet Res; 2020 Nov; 22(11):e23128. PubMed ID: 33035175
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Interpretable Machine Learning Model for Early Prediction of Mortality in ICU Patients with Rhabdomyolysis.
    Liu C; Liu X; Mao Z; Hu P; Li X; Hu J; Hong Q; Geng X; Chi K; Zhou F; Cai G; Chen X; Sun X
    Med Sci Sports Exerc; 2021 Sep; 53(9):1826-1834. PubMed ID: 33787533
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Explainable Machine Learning Model for Predicting GI Bleed Mortality in the Intensive Care Unit.
    Deshmukh F; Merchant SS
    Am J Gastroenterol; 2020 Oct; 115(10):1657-1668. PubMed ID: 32341266
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Illness severity assessment of older adults in critical illness using machine learning (ELDER-ICU): an international multicentre study with subgroup bias evaluation.
    Liu X; Hu P; Yeung W; Zhang Z; Ho V; Liu C; Dumontier C; Thoral PJ; Mao Z; Cao D; Mark RG; Zhang Z; Feng M; Li D; Celi LA
    Lancet Digit Health; 2023 Oct; 5(10):e657-e667. PubMed ID: 37599147
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Establishment and validation of a heart failure risk prediction model for elderly patients after coronary rotational atherectomy based on machine learning.
    Zhang L; Zhou X; Cao J
    PeerJ; 2024; 12():e16867. PubMed ID: 38313005
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Prediction model of in-hospital mortality in intensive care unit patients with cardiac arrest: a retrospective analysis of MIMIC -IV database based on machine learning.
    Sun Y; He Z; Ren J; Wu Y
    BMC Anesthesiol; 2023 May; 23(1):178. PubMed ID: 37231340
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Factor analysis based on SHapley Additive exPlanations for sepsis-associated encephalopathy in ICU mortality prediction using XGBoost - a retrospective study based on two large database.
    Guo J; Cheng H; Wang Z; Qiao M; Li J; Lyu J
    Front Neurol; 2023; 14():1290117. PubMed ID: 38162445
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Evaluate prognostic accuracy of SOFA component score for mortality among adults with sepsis by machine learning method.
    Pan X; Xie J; Zhang L; Wang X; Zhang S; Zhuang Y; Lin X; Shi S; Shi S; Lin W
    BMC Infect Dis; 2023 Feb; 23(1):76. PubMed ID: 36747139
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Use of Multiprognostic Index Domain Scores, Clinical Data, and Machine Learning to Improve 12-Month Mortality Risk Prediction in Older Hospitalized Patients: Prospective Cohort Study.
    Woodman RJ; Bryant K; Sorich MJ; Pilotto A; Mangoni AA
    J Med Internet Res; 2021 Jun; 23(6):e26139. PubMed ID: 34152274
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 25.