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 *

95 related articles for article (PubMed ID: 31438234)

  • 1. An Improvised Classification Model for Predicting Delirium.
    Veeranki SPK; Hayn D; Jauk S; Quehenberger F; Kramer D; Leodolter W; Schreier G
    Stud Health Technol Inform; 2019 Aug; 264():1566-1567. PubMed ID: 31438234
    [TBL] [Abstract][Full Text] [Related]  

  • 2. On the Representation of Machine Learning Results for Delirium Prediction in a Hospital Information System in Routine Care.
    Veeranki S; Hayn D; Eggerth A; Jauk S; Kramer D; Leodolter W; Schreier G
    Stud Health Technol Inform; 2018; 251():97-100. PubMed ID: 29968611
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Predicting postoperative delirium after microvascular decompression surgery with machine learning.
    Wang Y; Lei L; Ji M; Tong J; Zhou CM; Yang JJ
    J Clin Anesth; 2020 Nov; 66():109896. PubMed ID: 32504969
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Prediction of Incident Delirium Using a Random Forest classifier.
    Corradi JP; Thompson S; Mather JF; Waszynski CM; Dicks RS
    J Med Syst; 2018 Nov; 42(12):261. PubMed ID: 30430256
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients.
    Netzer M; Hackl WO; Schaller M; Alber L; Marksteiner J; Ammenwerth E
    Stud Health Technol Inform; 2020 Jun; 271():121-128. PubMed ID: 32578554
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Evaluating the Impact of Incorrect Diabetes Coding on the Performance of Multivariable Prediction Models.
    Jauk S; Kramer D; Schulz S; Leodolter W
    Stud Health Technol Inform; 2018; 251():249-252. PubMed ID: 29968650
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Information Adapted Machine Learning Models for Prediction in Clinical Workflow.
    Jauk S; Kramer D; Quehenberger F; Veeranki SPK; Hayn D; Schreier G; Leodolter W
    Stud Health Technol Inform; 2019; 260():65-72. PubMed ID: 31118320
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Delirium misdiagnosis risk in psychiatry: a machine learning-logistic regression predictive algorithm.
    Hercus C; Hudaib AR
    BMC Health Serv Res; 2020 Feb; 20(1):151. PubMed ID: 32106845
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Is Regular Re-Training of a Predictive Delirium Model Necessary After Deployment in Routine Care?
    Veeranki SPK; Kramer D; Hayn D; Jauk S; Eggerth A; Quehenberger F; Leodolter W; Schreier G
    Stud Health Technol Inform; 2019; 260():186-191. PubMed ID: 31118336
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Technology Acceptance of a Machine Learning Algorithm Predicting Delirium in a Clinical Setting: a Mixed-Methods Study.
    Jauk S; Kramer D; Avian A; Berghold A; Leodolter W; Schulz S
    J Med Syst; 2021 Mar; 45(4):48. PubMed ID: 33646459
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.
    Oh J; Cho D; Park J; Na SH; Kim J; Heo J; Shin CS; Kim JJ; Park JY; Lee B
    Physiol Meas; 2018 Mar; 39(3):035004. PubMed ID: 29376502
    [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. Predicting Depression Among Community Residing Older Adults: A Use of Machine Learning Approch.
    Choi J; Choi J; Choi WJ
    Stud Health Technol Inform; 2018; 250():265. PubMed ID: 29857458
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Machine Learning Approach for Investigating Delirium as a Multifactorial Syndrome.
    Ocagli H; Bottigliengo D; Lorenzoni G; Azzolina D; Acar AS; Sorgato S; Stivanello L; Degan M; Gregori D
    Int J Environ Res Public Health; 2021 Jul; 18(13):. PubMed ID: 34281037
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fetal health status prediction based on maternal clinical history using machine learning techniques.
    Akbulut A; Ertugrul E; Topcu V
    Comput Methods Programs Biomed; 2018 Sep; 163():87-100. PubMed ID: 30119860
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Can machine-learning improve cardiovascular risk prediction using routine clinical data?
    Weng SF; Reps J; Kai J; Garibaldi JM; Qureshi N
    PLoS One; 2017; 12(4):e0174944. PubMed ID: 28376093
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Applications of Machine Learning in Fatty Live Disease Prediction.
    Islam MM; Wu CC; Poly TN; Yang HC; Li YJ
    Stud Health Technol Inform; 2018; 247():166-170. PubMed ID: 29677944
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Enhanced neonatal surgical site infection prediction model utilizing statistically and clinically significant variables in combination with a machine learning algorithm.
    Bartz-Kurycki MA; Green C; Anderson KT; Alder AC; Bucher BT; Cina RA; Jamshidi R; Russell RT; Williams RF; Tsao K
    Am J Surg; 2018 Oct; 216(4):764-777. PubMed ID: 30078669
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of fatty liver disease using machine learning algorithms.
    Wu CC; Yeh WC; Hsu WD; Islam MM; Nguyen PAA; Poly TN; Wang YC; Yang HC; Jack Li YC
    Comput Methods Programs Biomed; 2019 Mar; 170():23-29. PubMed ID: 30712601
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Assessing Electronic Cigarette-Related Tweets for Sentiment and Content Using Supervised Machine Learning.
    Cole-Lewis H; Varghese A; Sanders A; Schwarz M; Pugatch J; Augustson E
    J Med Internet Res; 2015 Aug; 17(8):e208. PubMed ID: 26307512
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 5.