BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

310 related articles for article (PubMed ID: 34028357)

  • 1. Improving Current Glycated Hemoglobin Prediction in Adults: Use of Machine Learning Algorithms With Electronic Health Records.
    Alhassan Z; Watson M; Budgen D; Alshammari R; Alessa A; Al Moubayed N
    JMIR Med Inform; 2021 May; 9(5):e25237. PubMed ID: 34028357
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predicting Current Glycated Hemoglobin Levels in Adults From Electronic Health Records: Validation of Multiple Logistic Regression Algorithm.
    Alhassan Z; Budgen D; Alshammari R; Al Moubayed N
    JMIR Med Inform; 2020 Jul; 8(7):e18963. PubMed ID: 32618575
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Predicting mortality among patients with liver cirrhosis in electronic health records with machine learning.
    Guo A; Mazumder NR; Ladner DP; Foraker RE
    PLoS One; 2021; 16(8):e0256428. PubMed ID: 34464403
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Accurate Prediction of Coronary Heart Disease for Patients With Hypertension From Electronic Health Records With Big Data and Machine-Learning Methods: Model Development and Performance Evaluation.
    Du Z; Yang Y; Zheng J; Li Q; Lin D; Li Y; Fan J; Cheng W; Chen XH; Cai Y
    JMIR Med Inform; 2020 Jul; 8(7):e17257. PubMed ID: 32628616
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A data-driven approach to predicting diabetes and cardiovascular disease with machine learning.
    Dinh A; Miertschin S; Young A; Mohanty SD
    BMC Med Inform Decis Mak; 2019 Nov; 19(1):211. PubMed ID: 31694707
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predicting hospitalization following psychiatric crisis care using machine learning.
    Blankers M; van der Post LFM; Dekker JJM
    BMC Med Inform Decis Mak; 2020 Dec; 20(1):332. PubMed ID: 33302948
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Dynamic prediction of psychological treatment outcomes: development and validation of a prediction model using routinely collected symptom data.
    Bone C; Simmonds-Buckley M; Thwaites R; Sandford D; Merzhvynska M; Rubel J; Deisenhofer AK; Lutz W; Delgadillo J
    Lancet Digit Health; 2021 Apr; 3(4):e231-e240. PubMed ID: 33766287
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine Learning-Based Hospital Discharge Prediction for Patients With Cardiovascular Diseases: Development and Usability Study.
    Ahn I; Gwon H; Kang H; Kim Y; Seo H; Choi H; Cho HN; Kim M; Jun TJ; Kim YH
    JMIR Med Inform; 2021 Nov; 9(11):e32662. PubMed ID: 34787584
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Prediction of Prolonged Length of Hospital Stay After Cancer Surgery Using Machine Learning on Electronic Health Records: Retrospective Cross-sectional Study.
    Jo YY; Han J; Park HW; Jung H; Lee JD; Jung J; Cha HS; Sohn DK; Hwangbo Y
    JMIR Med Inform; 2021 Feb; 9(2):e23147. PubMed ID: 33616544
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.
    Taylor RA; Pare JR; Venkatesh AK; Mowafi H; Melnick ER; Fleischman W; Hall MK
    Acad Emerg Med; 2016 Mar; 23(3):269-78. PubMed ID: 26679719
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Early Detection of Septic Shock Onset Using Interpretable Machine Learners.
    Misra D; Avula V; Wolk DM; Farag HA; Li J; Mehta YB; Sandhu R; Karunakaran B; Kethireddy S; Zand R; Abedi V
    J Clin Med; 2021 Jan; 10(2):. PubMed ID: 33467539
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Using the H2O Automatic Machine Learning Algorithms to Identify Predictors of Web-Based Medical Record Nonuse Among Patients in a Data-Rich Environment: Mixed Methods Study.
    Chen Y; Liu X; Gao L; Zhu M; Shia BC; Chen M; Ye L; Qin L
    JMIR Med Inform; 2023 Jun; 11():e41576. PubMed ID: 37335616
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Prediction of Long-Term Stroke Recurrence Using Machine Learning Models.
    Abedi V; Avula V; Chaudhary D; Shahjouei S; Khan A; Griessenauer CJ; Li J; Zand R
    J Clin Med; 2021 Mar; 10(6):. PubMed ID: 33804724
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study.
    Lin H; Long E; Ding X; Diao H; Chen Z; Liu R; Huang J; Cai J; Xu S; Zhang X; Wang D; Chen K; Yu T; Wu D; Zhao X; Liu Z; Wu X; Jiang Y; Yang X; Cui D; Liu W; Zheng Y; Luo L; Wang H; Chan CC; Morgan IG; He M; Liu Y
    PLoS Med; 2018 Nov; 15(11):e1002674. PubMed ID: 30399150
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine learning outperforms traditional logistic regression and offers new possibilities for cardiovascular risk prediction: A study involving 143,043 Chinese patients with hypertension.
    Xi Y; Wang H; Sun N
    Front Cardiovasc Med; 2022; 9():1025705. PubMed ID: 36451926
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predicting Survival From Large Echocardiography and Electronic Health Record Datasets: Optimization With Machine Learning.
    Samad MD; Ulloa A; Wehner GJ; Jing L; Hartzel D; Good CW; Williams BA; Haggerty CM; Fornwalt BK
    JACC Cardiovasc Imaging; 2019 Apr; 12(4):681-689. PubMed ID: 29909114
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c.
    Ngufor C; Van Houten H; Caffo BS; Shah ND; McCoy RG
    J Biomed Inform; 2019 Jan; 89():56-67. PubMed ID: 30189255
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.
    Shirwaikar RD; Acharya U D; Makkithaya K; M S; Srivastava S; Lewis U LES
    Artif Intell Med; 2019 Jul; 98():59-76. PubMed ID: 31521253
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.