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Citing this Article

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Published on 17.01.17 in Vol 5, No 1 (2017): Jan-Mar

This paper is in the following e-collection/theme issue:

Works citing "Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill"

Joon Lee

JMIR Med Inform 2017 (Jan 17); 5(1):e3 

According to Crossref, the following articles are citing this article (DOI 10.2196/medinform.6690):

(note that this is only a small subset of citations)

  1. Magoev K, Krzhizhanovskaya VV, Kovalchuk SV. Application of clustering methods for detecting critical acute coronary syndrome patients. Procedia Computer Science 2018;136:370
    CrossRef
  2. Oikonomou EK, Williams MC, Kotanidis CP, Desai MY, Marwan M, Antonopoulos AS, Thomas KE, Thomas S, Akoumianakis I, Fan LM, Kesavan S, Herdman L, Alashi A, Centeno EH, Lyasheva M, Griffin BP, Flamm SD, Shirodaria C, Sabharwal N, Kelion A, Dweck MR, Van Beek EJR, Deanfield J, Hopewell JC, Neubauer S, Channon KM, Achenbach S, Newby DE, Antoniades C. A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography. European Heart Journal 2019;40(43):3529
    CrossRef
  3. Ahmed Z, Mohamed K, Zeeshan S, Dong X. Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database 2020;2020
    CrossRef
  4. Lin K, Hu Y, Kong G. Predicting in-hospital mortality of patients with acute kidney injury in the ICU using random forest model. International Journal of Medical Informatics 2019;125:55
    CrossRef
  5. Dai Z, Liu S, Wu J, Li M, Liu J, Li K, Beiki O. Analysis of adult disease characteristics and mortality on MIMIC-III. PLOS ONE 2020;15(4):e0232176
    CrossRef
  6. Rahman QA, Janmohamed T, Pirbaglou M, Clarke H, Ritvo P, Heffernan JM, Katz J. Defining and Predicting Pain Volatility in Users of the Manage My Pain App: Analysis Using Data Mining and Machine Learning Methods. Journal of Medical Internet Research 2018;20(11):e12001
    CrossRef
  7. Li Q, Xu Y. VS-GRU: A Variable Sensitive Gated Recurrent Neural Network for Multivariate Time Series with Massive Missing Values. Applied Sciences 2019;9(15):3041
    CrossRef
  8. Roy A, Bruce C, Schulte P, Olson L, Pola M. Failure prediction using personalized models and an application to heart failure prediction. Big Data Analytics 2020;5(1)
    CrossRef
  9. Tarekegn A, Ricceri F, Costa G, Ferracin E, Giacobini M. Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches. JMIR Medical Informatics 2020;8(6):e16678
    CrossRef
  10. Chicco D, Oneto L. Computational intelligence identifies alkaline phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival factors for hepatocellular carcinoma. Health Informatics Journal 2021;27(1):146045822098420
    CrossRef
  11. Alshwaheen TI, Hau YW, Ass'Ad N, Abualsamen MM. A Novel and Reliable Framework of Patient Deterioration Prediction in Intensive Care Unit Based on Long Short-Term Memory-Recurrent Neural Network. IEEE Access 2021;9:3894
    CrossRef
  12. Wu W, Li Y, Feng A, Li L, Huang T, Xu A, Lyu J. Data mining in clinical big data: the frequently used databases, steps, and methodological models. Military Medical Research 2021;8(1)
    CrossRef
  13. Yen JM, Lim JH. A Clinical Perspective on Bespoke Sensing Mechanisms for Remote Monitoring and Rehabilitation of Neurological Diseases: Scoping Review. Sensors 2023;23(1):536
    CrossRef
  14. Cornelius E, Akman O, Hrozencik D. COVID-19 Mortality Prediction Using Machine Learning-Integrated Random Forest Algorithm under Varying Patient Frailty. Mathematics 2021;9(17):2043
    CrossRef
  15. . Artificial intelligence and machine learning in precision and genomic medicine. Medical Oncology 2022;39(8)
    CrossRef
  16. Lopez Pineda A, Pourshafeie A, Ioannidis A, Leibold CM, Chan AL, Bustamante CD, Frankovich J, Wojcik GL. Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients. Journal of Biomedical Informatics 2021;113:103664
    CrossRef
  17. Zhang F, Luo C, Lan C, Zhan J. Benchmarking feature selection methods with different prediction models on large-scale healthcare event data. BenchCouncil Transactions on Benchmarks, Standards and Evaluations 2021;1(1):100004
    CrossRef
  18. Cengil AB, Eksioglu B, Eksioglu S, Eswaran H, Hayes CJ, Bogulski CA. Using data analytics for telehealth utilization: A case study in Arkansas. Journal of Telemedicine and Telecare 2023;:1357633X2311600
    CrossRef
  19. Ilhan Taskin Z, Yildirak K, Aladag CH. An enhanced random forest approach using CoClust clustering: MIMIC-III and SMS spam collection application. Journal of Big Data 2023;10(1)
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/medinform.6690):

  1. Berikol GB, Berikol G. Artificial Intelligence in Precision Health. 2020. :177
    CrossRef
  2. Miranda E, Kumbangsila M, Aryuni M, Richard , Zakiyyah AY, Sano AVD. Proceeding of the 3rd International Conference on Electronics, Biomedical Engineering, and Health Informatics. 2023. Chapter 11:145
    CrossRef