Informing the Design of Individualized Self-Management Regimens from the Human, Data, and Machine Learning Perspectives.
- DOI
- 10.1145/3717063
- Published
- 2025 Aug
- Container
- ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery
- 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:10.1145/3717063,
title = {Informing the Design of Individualized Self-Management Regimens from the Human, Data, and Machine Learning Perspectives.},
author = {Pichon A and Urteaga I and Mamykina L and Elhadad N},
year = {2025},
journal = {ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery},
doi = {10.1145/3717063},
url = {https://doi.org/10.1145/3717063}
}RIS
TY - JOUR TI - Informing the Design of Individualized Self-Management Regimens from the Human, Data, and Machine Learning Perspectives. AU - Pichon A AU - Urteaga I AU - Mamykina L AU - Elhadad N PY - 2025 JO - ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery DO - 10.1145/3717063 UR - https://doi.org/10.1145/3717063 ER -
APA
A, P., I, U., L, M., & N, E. (2025). Informing the Design of Individualized Self-Management Regimens from the Human, Data, and Machine Learning Perspectives.. ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery. https://doi.org/10.1145/3717063
Source records
- pubmed · retrieved 2026-09-24T21:41:01.874Z