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

Machine Learning (1370) Clinical Information and Decision Making (1314) Big Data Analytics for Elder Care (20) Falls Prevention in the Elderly (64) Geroinformatics and Electronic Clinical Information/Decision Making in Geriatrics (17) Frailty Detection, Assessment and Prediction (19)

Published on in Vol 8, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16678, first published .
Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches

Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches

Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches

Authors of this article:

Adane Tarekegn1 Author Orcid Image ;   Fulvio Ricceri2, 3 Author Orcid Image ;   Giuseppe Costa2, 3 Author Orcid Image ;   Elisa Ferracin3 Author Orcid Image ;   Mario Giacobini4 Author Orcid Image
Article Authors Cited by (35) Tweetations (7) Metrics

Journals

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  2. Tarekegn A, Giacobini M, Michalak K. A review of methods for imbalanced multi-label classification. Pattern Recognition 2021;118:107965 View
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  11. Sepúlveda M, Arauna D, García F, Albala C, Palomo I, Fuentes E. Frailty in Aging and the Search for the Optimal Biomarker: A Review. Biomedicines 2022;10(6):1426 View
  12. Wang J, Wang S, Zhu M, Yang T, Yin Q, Hou Y. Risk Prediction of Major Adverse Cardiovascular Events Occurrence Within 6 Months After Coronary Revascularization: Machine Learning Study. JMIR Medical Informatics 2022;10(4):e33395 View
  13. Heyl J, Hardy F, Tucker K, Hopper A, Marchã M, Navaratnam A, Briggs T, Yates J, Day J, Wheeler A, Eve-Jones S, Gray W. Frailty, Comorbidity, and Associations With In-Hospital Mortality in Older COVID-19 Patients: Exploratory Study of Administrative Data. Interactive Journal of Medical Research 2022;11(2):e41520 View
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  15. Martin J, Crane-Droesch A, Lapite F, Puhl J, Kmiec T, Silvestri J, Ungar L, Kinosian B, Himes B, Hubbard R, Diamond J, Ahya V, Sims M, Halpern S, Weissman G. Development and validation of a prediction model for actionable aspects of frailty in the text of clinicians’ encounter notes. Journal of the American Medical Informatics Association 2021;29(1):109 View
  16. Wu Y, Jia M, Xiang C, Fang Y. Latent trajectories of frailty and risk prediction models among geriatric community dwellers: an interpretable machine learning perspective. BMC Geriatrics 2022;22(1) View
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  21. Liu Q, Yang L, Shi Z, Yu J, Si H, Jin Y, Bian Y, Li Y, Ji L, Qiao X, Wang W, Liu H, Zhang M, Wang C. Development and validation of a preliminary clinical support system for measuring the probability of incident 2-year (pre)frailty among community-dwelling older adults: A prospective cohort study. International Journal of Medical Informatics 2023;177:105138 View
  22. Fan S, Ye J, Xu Q, Peng R, Hu B, Pei Z, Yang Z, Xu F. Digital health technology combining wearable gait sensors and machine learning improve the accuracy in prediction of frailty. Frontiers in Public Health 2023;11 View
  23. Velazquez-Diaz D, Arco J, Ortiz A, Pérez-Cabezas V, Lucena-Anton D, Moral-Munoz J, Galán-Mercant A. Use of Artificial Intelligence in the Identification and Diagnosis of Frailty Syndrome in Older Adults: Scoping Review. Journal of Medical Internet Research 2023;25:e47346 View
  24. Du Y, Huang W. Portfolio Allocation with Medical Expenditure Risk-A Life Cycle Model and Machine Learning Analysis. Journal of Regional Economics 2023;2(1) View
  25. Bai A, Zhao M, Zhang T, Yang C, Yan J, Wang G, Zhang P, Xu W, Hu Y. Development and validation of a nomogram-assisted tool to predict potentially reversible cognitive frailty in Chinese community-living older adults. Aging Clinical and Experimental Research 2023;35(10):2145 View
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  28. Tarekegn A, Sajjad M, Cheikh F, Ullah M, Muhammad K. Efficient Human Gait Activity Recognition Based on Sensor Fusion and Intelligent Stacking Framework. IEEE Sensors Journal 2023;23(22):28355 View
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Books/Policy Documents

  1. Nega Tarekegn A, Alaya Cheikh F, Sajjad M, Ullah M. Artificial Intelligence and Soft Computing. View