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AI-enabled proactive mHealth with automated decision-making
发表日期 March 28, 2023 (DOI: https://doi.org/10.54985/peeref.2303p9916446)
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作者
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Muhammad Sulaiman1
- UiT The Arctic University of Norway
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会议/活动
- Nordic AI-meet 2021, November 2021 (Oslo, Norway)
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海报摘要
- The goal presented in this poster is to establish AI-enabled proactive mHealth to predict and prevent a situation promptly. With automated decision-making powered by predictive analytics to support users on accurate decisions instantly. A personalized system, that considers the uniqueness of a user. The main contribution is to establish a core framework of proactive mHealth It includes machine learning algorithms such as support vector machine (SVM), random forest (RF), decision trees (DT), regression models, artificial neural network (ANN) etc., to provide automated decision-making (ADM).
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关键词
- MHealth, Artificial intelligence, Proactive health, Wearables, Automed decision-making
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研究领域
- Computer and Information Science , Bioinformatics and Genomics
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参考文献
- 暂无数据
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基金
- 暂无数据
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补充材料
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附加信息
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- 利益冲突
- No competing interests were disclosed.
- 数据可用性声明
- Data sharing not applicable to this poster as no datasets were generated or analyzed during the current study.
- 知识共享许可协议
- Copyright © 2023 Sulaiman. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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引用
Sulaiman, M. AI-enabled proactive mHealth with automated decision-making [not peer reviewed]. Peeref 2023 (poster).
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