BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

167 related articles for article (PubMed ID: 37494080)

  • 1. Comparing Explainable Machine Learning Approaches With Traditional Statistical Methods for Evaluating Stroke Risk Models: Retrospective Cohort Study.
    Lolak S; Attia J; McKay GJ; Thakkinstian A
    JMIR Cardio; 2023 Jul; 7():e47736. PubMed ID: 37494080
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.
    Herrin J; Abraham NS; Yao X; Noseworthy PA; Inselman J; Shah ND; Ngufor C
    JAMA Netw Open; 2021 May; 4(5):e2110703. PubMed ID: 34019087
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of incident atrial fibrillation in post-stroke patients using machine learning: a French nationwide study.
    Bisson A; Lemrini Y; El-Bouri W; Bodin A; Angoulvant D; Lip GYH; Fauchier L
    Clin Res Cardiol; 2023 Jun; 112(6):815-823. PubMed ID: 36527472
    [TBL] [Abstract][Full Text] [Related]  

  • 4. XGBoost, A Novel Explainable AI Technique, in the Prediction of Myocardial Infarction: A UK Biobank Cohort Study.
    Moore A; Bell M
    Clin Med Insights Cardiol; 2022; 16():11795468221133611. PubMed ID: 36386405
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An accurate and explainable ensemble learning method for carotid plaque prediction in an asymptomatic population.
    Wu D; Cui G; Huang X; Chen Y; Liu G; Ren L; Li Y
    Comput Methods Programs Biomed; 2022 Jun; 221():106842. PubMed ID: 35569238
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Explainable Machine Learning Techniques To Predict Amiodarone-Induced Thyroid Dysfunction Risk: Multicenter, Retrospective Study With External Validation.
    Lu YT; Chao HJ; Chiang YC; Chen HY
    J Med Internet Res; 2023 Feb; 25():e43734. PubMed ID: 36749620
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A proposed tree-based explainable artificial intelligence approach for the prediction of angina pectoris.
    Guldogan E; Yagin FH; Pinar A; Colak C; Kadry S; Kim J
    Sci Rep; 2023 Dec; 13(1):22189. PubMed ID: 38092844
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine Learning Approaches for Predicting Hypertension and Its Associated Factors Using Population-Level Data From Three South Asian Countries.
    Islam SMS; Talukder A; Awal MA; Siddiqui MMU; Ahamad MM; Ahammed B; Rawal LB; Alizadehsani R; Abawajy J; Laranjo L; Chow CK; Maddison R
    Front Cardiovasc Med; 2022; 9():839379. PubMed ID: 35433854
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting post-stroke pneumonia using deep neural network approaches.
    Ge Y; Wang Q; Wang L; Wu H; Peng C; Wang J; Xu Y; Xiong G; Zhang Y; Yi Y
    Int J Med Inform; 2019 Dec; 132():103986. PubMed ID: 31629312
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Explainable SHAP-XGBoost models for in-hospital mortality after myocardial infarction.
    Tarabanis C; Kalampokis E; Khalil M; Alviar CL; Chinitz LA; Jankelson L
    Cardiovasc Digit Health J; 2023 Aug; 4(4):126-132. PubMed ID: 37600443
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Explainable machine learning for chronic lymphocytic leukemia treatment prediction using only inexpensive tests.
    Meiseles A; Paley D; Ziv M; Hadid Y; Rokach L; Tadmor T
    Comput Biol Med; 2022 Jun; 145():105490. PubMed ID: 35405402
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning-based analysis of risk factors for atrial fibrillation recurrence after Cox-Maze IV procedure in patients with atrial fibrillation and chronic valvular disease: A retrospective cohort study with a control group.
    Jiang Z; Song L; Liang C; Zhang H; Tan H; Sun Y; Guo R; Liu L
    Front Cardiovasc Med; 2023; 10():1140670. PubMed ID: 37034340
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study.
    Bae SW; Suffoletto B; Zhang T; Chung T; Ozolcer M; Islam MR; Dey AK
    JMIR Form Res; 2023 May; 7():e39862. PubMed ID: 36809294
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Explainable machine learning for long-term outcome prediction in two-center stroke patients after intravenous thrombolysis.
    Ping Z; Huiyu S; Min L; Qingke B; Qiuyun L; Xu C
    Front Neurosci; 2023; 17():1146197. PubMed ID: 36908783
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Risk Prediction of Diabetic Foot Amputation Using Machine Learning and Explainable Artificial Intelligence.
    Oei CW; Chan YM; Zhang X; Leo KH; Yong E; Chong RC; Hong Q; Zhang L; Pan Y; Tan GWL; Mak MHW
    J Diabetes Sci Technol; 2024 Jan; ():19322968241228606. PubMed ID: 38288696
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Explainable ensemble machine learning model for prediction of 28-day mortality risk in patients with sepsis-associated acute kidney injury.
    Yang J; Peng H; Luo Y; Zhu T; Xie L
    Front Med (Lausanne); 2023; 10():1165129. PubMed ID: 37275353
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. Explainable machine learning model reveals its decision-making process in identifying patients with paroxysmal atrial fibrillation at high risk for recurrence after catheter ablation.
    Ma Y; Zhang D; Xu J; Pang H; Hu M; Li J; Zhou S; Guo L; Yi F
    BMC Cardiovasc Disord; 2023 Feb; 23(1):91. PubMed ID: 36803424
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [Construction of a predictive model for in-hospital mortality of sepsis patients in intensive care unit based on machine learning].
    Zhu M; Hu C; He Y; Qian Y; Tang S; Hu Q; Hao C
    Zhonghua Wei Zhong Bing Ji Jiu Yi Xue; 2023 Jul; 35(7):696-701. PubMed ID: 37545445
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.