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 *

126 related articles for article (PubMed ID: 33800877)

  • 1. A Novel Machine Learning Strategy for the Prediction of Antihypertensive Peptides Derived from Food with High Efficiency.
    Wang L; Niu D; Wang X; Khan J; Shen Q; Xue Y
    Foods; 2021 Mar; 10(3):. PubMed ID: 33800877
    [TBL] [Abstract][Full Text] [Related]  

  • 2. XGBoost, a Machine Learning Method, Predicts Neurological Recovery in Patients with Cervical Spinal Cord Injury.
    Inoue T; Ichikawa D; Ueno T; Cheong M; Inoue T; Whetstone WD; Endo T; Nizuma K; Tominaga T
    Neurotrauma Rep; 2020; 1(1):8-16. PubMed ID: 34223526
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of Type 2 Diabetes Risk and Its Effect Evaluation Based on the XGBoost Model.
    Wang L; Wang X; Chen A; Jin X; Che H
    Healthcare (Basel); 2020 Jul; 8(3):. PubMed ID: 32751894
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Comparative Analysis of Novel Deep Learning and Ensemble Learning Models to Predict the Allergenicity of Food Proteins.
    Wang L; Niu D; Zhao X; Wang X; Hao M; Che H
    Foods; 2021 Apr; 10(4):. PubMed ID: 33918556
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A Machine-Learning-Based Prediction Method for Hypertension Outcomes Based on Medical Data.
    Chang W; Liu Y; Xiao Y; Yuan X; Xu X; Zhang S; Zhou S
    Diagnostics (Basel); 2019 Nov; 9(4):. PubMed ID: 31703364
    [TBL] [Abstract][Full Text] [Related]  

  • 6. An optimized XGBoost-based machine learning method for predicting wave run-up on a sloping beach.
    Tarwidi D; Pudjaprasetya SR; Adytia D; Apri M
    MethodsX; 2023; 10():102119. PubMed ID: 37007622
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting the Tool Wear of a Drilling Process Using Novel Machine Learning XGBoost-SDA.
    Alajmi MS; Almeshal AM
    Materials (Basel); 2020 Nov; 13(21):. PubMed ID: 33158099
    [TBL] [Abstract][Full Text] [Related]  

  • 8. On the Use of Machine Learning Models for Prediction of Compressive Strength of Concrete: Influence of Dimensionality Reduction on the Model Performance.
    Wan Z; Xu Y; Ĺ avija B
    Materials (Basel); 2021 Feb; 14(4):. PubMed ID: 33546376
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predictive Utility of a Machine Learning Algorithm in Estimating Mortality Risk in Cardiac Surgery.
    Kilic A; Goyal A; Miller JK; Gjekmarkaj E; Tam WL; Gleason TG; Sultan I; Dubrawksi A
    Ann Thorac Surg; 2020 Jun; 109(6):1811-1819. PubMed ID: 31706872
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deep learning drives efficient discovery of novel antihypertensive peptides from soybean protein isolate.
    Zhang Y; Dai Z; Zhao X; Chen C; Li S; Meng Y; Suonan Z; Sun Y; Shen Q; Wang L; Xue Y
    Food Chem; 2023 Mar; 404(Pt B):134690. PubMed ID: 36323032
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Discovery of Depression-Associated Factors From a Nationwide Population-Based Survey: Epidemiological Study Using Machine Learning and Network Analysis.
    Nam SM; Peterson TA; Seo KY; Han HW; Kang JI
    J Med Internet Res; 2021 Jun; 23(6):e27344. PubMed ID: 34184998
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.
    Vaid A; Somani S; Russak AJ; De Freitas JK; Chaudhry FF; Paranjpe I; Johnson KW; Lee SJ; Miotto R; Richter F; Zhao S; Beckmann ND; Naik N; Kia A; Timsina P; Lala A; Paranjpe M; Golden E; Danieletto M; Singh M; Meyer D; O'Reilly PF; Huckins L; Kovatch P; Finkelstein J; Freeman RM; Argulian E; Kasarskis A; Percha B; Aberg JA; Bagiella E; Horowitz CR; Murphy B; Nestler EJ; Schadt EE; Cho JH; Cordon-Cardo C; Fuster V; Charney DS; Reich DL; Bottinger EP; Levin MA; Narula J; Fayad ZA; Just AC; Charney AW; Nadkarni GN; Glicksberg BS
    J Med Internet Res; 2020 Nov; 22(11):e24018. PubMed ID: 33027032
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Detecting Examinees With Item Preknowledge in Large-Scale Testing Using Extreme Gradient Boosting (XGBoost).
    Zopluoglu C
    Educ Psychol Meas; 2019 Oct; 79(5):931-961. PubMed ID: 31488920
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Copy number variation in plasma as a tool for lung cancer prediction using Extreme Gradient Boosting (XGBoost) classifier.
    Yu D; Liu Z; Su C; Han Y; Duan X; Zhang R; Liu X; Yang Y; Xu S
    Thorac Cancer; 2020 Jan; 11(1):95-102. PubMed ID: 31694073
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Machine Learning for the Prediction of Red Blood Cell Transfusion in Patients During or After Liver Transplantation Surgery.
    Liu LP; Zhao QY; Wu J; Luo YW; Dong H; Chen ZW; Gui R; Wang YJ
    Front Med (Lausanne); 2021; 8():632210. PubMed ID: 33693019
    [No Abstract]   [Full Text] [Related]  

  • 16. Prediction of Glucose Metabolism Disorder Risk Using a Machine Learning Algorithm: Pilot Study.
    Maeta K; Nishiyama Y; Fujibayashi K; Gunji T; Sasabe N; Iijima K; Naito T
    JMIR Diabetes; 2018 Nov; 3(4):e10212. PubMed ID: 30478026
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Ensemble-AHTPpred: A Robust Ensemble Machine Learning Model Integrated With a New Composite Feature for Identifying Antihypertensive Peptides.
    Lertampaiporn S; Hongsthong A; Wattanapornprom W; Thammarongtham C
    Front Genet; 2022; 13():883766. PubMed ID: 35571042
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Prediction of death status on the course of treatment in SARS-COV-2 patients with deep learning and machine learning methods.
    Kivrak M; Guldogan E; Colak C
    Comput Methods Programs Biomed; 2021 Apr; 201():105951. PubMed ID: 33513487
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Machine learning-based models to support decision-making in emergency department triage for patients with suspected cardiovascular disease.
    Jiang H; Mao H; Lu H; Lin P; Garry W; Lu H; Yang G; Rainer TH; Chen X
    Int J Med Inform; 2021 Jan; 145():104326. PubMed ID: 33197878
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.