Published on in Vol 9, No 2 (2021): February
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/25655, first published
.
Journals
- Elnakib S, Vecino-Ortiz A, Gibson D, Agarwal S, Trujillo A, Zhu Y, Labrique A. A Novel Score for mHealth Apps to Predict and Prevent Mortality: Further Validation and Adaptation to the US Population Using the US National Health and Nutrition Examination Survey Data Set. Journal of Medical Internet Research 2022;24(6):e36787 View
- Tedesco S, Andrulli M, Larsson M, Kelly D, Alamäki A, Timmons S, Barton J, Condell J, O’Flynn B, Nordström A. Comparison of Machine Learning Techniques for Mortality Prediction in a Prospective Cohort of Older Adults. International Journal of Environmental Research and Public Health 2021;18(23):12806 View
- Li Z, Yang N, He L, Wang J, Ping F, Li W, Xu L, Zhang H, Li Y. Development and validation of questionnaire-based machine learning models for predicting all-cause mortality in a representative population of China. Frontiers in Public Health 2023;11 View
- Bruun-Rasmussen N, Napolitano G, Bojesen S, Ellervik C, Holmager T, Rasmussen K, Lynge E. Correlation between allostatic load index and cumulative mortality: a register-based study of Danish municipalities. BMJ Open 2024;14(2):e075697 View
Books/Policy Documents
- Rajamani S, Iyer R. Convergence of Antenna Technologies, Electronics, and AI. View