BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

134 related articles for article (PubMed ID: 35677098)

  • 1. Integrated Learning Model-Based Assessment of Enteral Nutrition Support in Neurosurgical Intensive Care Patients.
    Jiang S; Wang R; Zhang H
    Biomed Res Int; 2022; 2022():4061043. PubMed ID: 35677098
    [TBL] [Abstract][Full Text] [Related]  

  • 2. [Prediction of intensive care unit readmission for critically ill patients based on ensemble learning].
    Lin Y; Wu JY; Lin K; Hu YH; Kong GL
    Beijing Da Xue Xue Bao Yi Xue Ban; 2021 Jun; 53(3):566-572. PubMed ID: 34145862
    [TBL] [Abstract][Full Text] [Related]  

  • 3. [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]  

  • 4. Biological signatures and prediction of an immunosuppressive status-persistent critical illness-among orthopedic trauma patients using machine learning techniques.
    Lei M; Han Z; Wang S; Guo C; Zhang X; Song Y; Lin F; Huang T
    Front Immunol; 2022; 13():979877. PubMed ID: 36325351
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
    Anderson AB; Grazal CF; Balazs GC; Potter BK; Dickens JF; Forsberg JA
    Clin Orthop Relat Res; 2020 Jul; 478(7):0-1618. PubMed ID: 32282466
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Feeding the critically ill obese patient: a systematic review protocol.
    Secombe P; Harley S; Chapman M; Aromataris E
    JBI Database System Rev Implement Rep; 2015 Oct; 13(10):95-109. PubMed ID: 26571286
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Comparison and development of machine learning for thalidomide-induced peripheral neuropathy prediction of refractory Crohn's disease in Chinese population.
    Mao J; Chao K; Jiang FL; Ye XP; Yang T; Li P; Zhu X; Hu PJ; Zhou BJ; Huang M; Gao X; Wang XD
    World J Gastroenterol; 2023 Jun; 29(24):3855-3870. PubMed ID: 37426324
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Predicting Prolonged Length of ICU Stay through Machine Learning.
    Wu J; Lin Y; Li P; Hu Y; Zhang L; Kong G
    Diagnostics (Basel); 2021 Nov; 11(12):. PubMed ID: 34943479
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A prediction model of enteral nutrition complicated with severe diarrhea in ICU patients based on CD55.
    Xie Y; Tian R; Wang T; Jin W; Hou Y; Zhou Z; Wang R
    Ann Palliat Med; 2021 Feb; 10(2):1610-1619. PubMed ID: 33222452
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. Machine learning prediction of postoperative major adverse cardiovascular events in geriatric patients: a prospective cohort study.
    Peng X; Zhu T; Wang T; Wang F; Li K; Hao X
    BMC Anesthesiol; 2022 Sep; 22(1):284. PubMed ID: 36088288
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A machine learning-based prediction model for in-hospital mortality among critically ill patients with hip fracture: An internal and external validated study.
    Lei M; Han Z; Wang S; Han T; Fang S; Lin F; Huang T
    Injury; 2023 Feb; 54(2):636-644. PubMed ID: 36414503
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Contrast between traditional and machine learning algorithms based on a urine culture predictive model: a multicenter retrospective study in patients with urinary calculi.
    He Y; Peng P; Ying W; Wang Q; Wang Y; Liu X; Song W; Gao Y; Li P; Wang J; Zhu W; Gao W; Zhou X; Li X; Zhou L
    Transl Androl Urol; 2022 Feb; 11(2):139-148. PubMed ID: 35280663
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Nutrition of the critically ill patient and effects of implementing a nutritional support algorithm in ICU.
    Wøien H; Bjørk IT
    J Clin Nurs; 2006 Feb; 15(2):168-77. PubMed ID: 16422734
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Development and validation of a machine learning algorithm-based risk prediction model of pressure injury in the intensive care unit.
    Xu J; Chen D; Deng X; Pan X; Chen Y; Zhuang X; Sun C
    Int Wound J; 2022 Nov; 19(7):1637-1649. PubMed ID: 35077000
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.