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.
228 related articles for article (PubMed ID: 29718407)
1. Design and implementation of a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. Reps JM; Schuemie MJ; Suchard MA; Ryan PB; Rijnbeek PR J Am Med Inform Assoc; 2018 Aug; 25(8):969-975. PubMed ID: 29718407 [TBL] [Abstract][Full Text] [Related]
2. Using Iterative Pairwise External Validation to Contextualize Prediction Model Performance: A Use Case Predicting 1-Year Heart Failure Risk in Patients with Diabetes Across Five Data Sources. Williams RD; Reps JM; Kors JA; Ryan PB; Steyerberg E; Verhamme KM; Rijnbeek PR Drug Saf; 2022 May; 45(5):563-570. PubMed ID: 35579818 [TBL] [Abstract][Full Text] [Related]
3. A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data. Ahmadi N; Nguyen QV; Sedlmayr M; Wolfien M Sci Rep; 2024 Jan; 14(1):2287. PubMed ID: 38280887 [TBL] [Abstract][Full Text] [Related]
4. A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data. Khalid S; Yang C; Blacketer C; Duarte-Salles T; Fernández-Bertolín S; Kim C; Park RW; Park J; Schuemie MJ; Sena AG; Suchard MA; You SC; Rijnbeek PR; Reps JM Comput Methods Programs Biomed; 2021 Nov; 211():106394. PubMed ID: 34560604 [TBL] [Abstract][Full Text] [Related]
5. Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research. Schuemie M; Reps J; Black A; Defalco F; Evans L; Fridgeirsson E; Gilbert JP; Knoll C; Lavallee M; Rao GA; Rijnbeek P; Sadowski K; Sena A; Swerdel J; Williams RD; Suchard M Stud Health Technol Inform; 2024 Jan; 310():966-970. PubMed ID: 38269952 [TBL] [Abstract][Full Text] [Related]
6. KETOS: Clinical decision support and machine learning as a service - A training and deployment platform based on Docker, OMOP-CDM, and FHIR Web Services. Gruendner J; Schwachhofer T; Sippl P; Wolf N; Erpenbeck M; Gulden C; Kapsner LA; Zierk J; Mate S; Stürzl M; Croner R; Prokosch HU; Toddenroth D PLoS One; 2019; 14(10):e0223010. PubMed ID: 31581246 [TBL] [Abstract][Full Text] [Related]
7. Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients. Colubri A; Silver T; Fradet T; Retzepi K; Fry B; Sabeti P PLoS Negl Trop Dis; 2016 Mar; 10(3):e0004549. PubMed ID: 26991501 [TBL] [Abstract][Full Text] [Related]
8. Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models. Yousefi S; Amrollahi F; Amgad M; Dong C; Lewis JE; Song C; Gutman DA; Halani SH; Velazquez Vega JE; Brat DJ; Cooper LAD Sci Rep; 2017 Sep; 7(1):11707. PubMed ID: 28916782 [TBL] [Abstract][Full Text] [Related]
9. The effectiveness of internet-based e-learning on clinician behavior and patient outcomes: a systematic review protocol. Sinclair P; Kable A; Levett-Jones T JBI Database System Rev Implement Rep; 2015 Jan; 13(1):52-64. PubMed ID: 26447007 [TBL] [Abstract][Full Text] [Related]
10. Learning patient-level prediction models across multiple healthcare databases: evaluation of ensembles for increasing model transportability. Reps JM; Williams RD; Schuemie MJ; Ryan PB; Rijnbeek PR BMC Med Inform Decis Mak; 2022 May; 22(1):142. PubMed ID: 35614485 [TBL] [Abstract][Full Text] [Related]
11. Development and validation of phenotype classifiers across multiple sites in the observational health data sciences and informatics network. Kashyap M; Seneviratne M; Banda JM; Falconer T; Ryu B; Yoo S; Hripcsak G; Shah NH J Am Med Inform Assoc; 2020 Jun; 27(6):877-883. PubMed ID: 32374408 [TBL] [Abstract][Full Text] [Related]
12. Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework. Layeghian Javan S; Sepehri MM; Aghajani H J Biomed Inform; 2018 Dec; 88():70-89. PubMed ID: 30389440 [TBL] [Abstract][Full Text] [Related]
13. Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data. Samper-González J; Burgos N; Bottani S; Fontanella S; Lu P; Marcoux A; Routier A; Guillon J; Bacci M; Wen J; Bertrand A; Bertin H; Habert MO; Durrleman S; Evgeniou T; Colliot O; ; Neuroimage; 2018 Dec; 183():504-521. PubMed ID: 30130647 [TBL] [Abstract][Full Text] [Related]
14. A Semantic Transformation Methodology for the Secondary Use of Observational Healthcare Data in Postmarketing Safety Studies. Pacaci A; Gonul S; Sinaci AA; Yuksel M; Laleci Erturkmen GB Front Pharmacol; 2018; 9():435. PubMed ID: 29760661 [No Abstract] [Full Text] [Related]
15. Trajectories: a framework for detecting temporal clinical event sequences from health data standardized to the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Künnapuu K; Ioannou S; Ligi K; Kolde R; Laur S; Vilo J; Rijnbeek PR; Reisberg S JAMIA Open; 2022 Apr; 5(1):ooac021. PubMed ID: 35571357 [TBL] [Abstract][Full Text] [Related]
16. POPCORN: A web service for individual PrognOsis prediction based on multi-center clinical data CollabORatioN without patient-level data sharing. Tian Y; Shang Y; Tong DY; Chi SQ; Li J; Kong XX; Ding KF; Li JS J Biomed Inform; 2018 Oct; 86():1-14. PubMed ID: 30103028 [TBL] [Abstract][Full Text] [Related]
17. Predictive analytics in health care: how can we know it works? Van Calster B; Wynants L; Timmerman D; Steyerberg EW; Collins GS J Am Med Inform Assoc; 2019 Dec; 26(12):1651-1654. PubMed ID: 31373357 [TBL] [Abstract][Full Text] [Related]
18. Constructing query-driven dynamic machine learning model with application to protein-ligand binding sites prediction. Yu DJ; Hu J; Li QM; Tang ZM; Yang JY; Shen HB IEEE Trans Nanobioscience; 2015 Jan; 14(1):45-58. PubMed ID: 25730499 [TBL] [Abstract][Full Text] [Related]
19. Patient-Level Fall Risk Prediction Using the Observational Medical Outcomes Partnership's Common Data Model: Pilot Feasibility Study. Jung H; Yoo S; Kim S; Heo E; Kim B; Lee HY; Hwang H JMIR Med Inform; 2022 Mar; 10(3):e35104. PubMed ID: 35275076 [TBL] [Abstract][Full Text] [Related]
20. Can Machine Learning Methods Produce Accurate and Easy-to-use Prediction Models of 30-day Complications and Mortality After Knee or Hip Arthroplasty? Harris AHS; Kuo AC; Weng Y; Trickey AW; Bowe T; Giori NJ Clin Orthop Relat Res; 2019 Feb; 477(2):452-460. PubMed ID: 30624314 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]