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. 2023 Feb 13;25:e44238. doi: 10.2196/44238

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©Liuyang Yang, Gang Li, Jin Yang, Ting Zhang, Jing Du, Tian Liu, Xingxing Zhang, Xuan Han, Wei Li, Libing Ma, Luzhao Feng, Weizhong Yang. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.02.2023.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Structure of the multiattention deep-learning model (MAL) based on long short-term memory (LSTM). Schematic diagram representing multisource heterogeneous data input to the MAL model, including climate, Baidu searrch, demography, and other data. The curves of five independent variables are displayed: maximum temperature per week (Tmax), mean relative humidity per week (Hmean), mean precipitation per week, the mean temperature difference per week (dT; Tmax–Tmin), and air quality index (AQI).