Editorial: Artificial intelligence, machine learning, and data-mining techniques to increase cost-effectiveness in healthcare.
- DOI
- 10.3389/fpubh.2024.1525628
- Published
- 2024
- Container
- Frontiers in public health
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.3389/fpubh.2024.1525628,
title = {Editorial: Artificial intelligence, machine learning, and data-mining techniques to increase cost-effectiveness in healthcare.},
author = {Jeanty PW and Narcisse MR and Crastes Dit Sourd R},
year = {2024},
journal = {Frontiers in public health},
doi = {10.3389/fpubh.2024.1525628},
url = {https://doi.org/10.3389/fpubh.2024.1525628}
}RIS
TY - JOUR TI - Editorial: Artificial intelligence, machine learning, and data-mining techniques to increase cost-effectiveness in healthcare. AU - Jeanty PW AU - Narcisse MR AU - Crastes Dit Sourd R PY - 2024 JO - Frontiers in public health DO - 10.3389/fpubh.2024.1525628 UR - https://doi.org/10.3389/fpubh.2024.1525628 ER -
APA
PW, J., MR, N., & R, C. D. S. (2024). Editorial: Artificial intelligence, machine learning, and data-mining techniques to increase cost-effectiveness in healthcare.. Frontiers in public health. https://doi.org/10.3389/fpubh.2024.1525628
Source records
- pubmed · retrieved 2026-09-25T08:41:39.746Z