Social media posts and transformer-based models for early detection of heat stroke
Peer-Reviewed Publication
Updates every hour. Last Updated: 6-May-2025 18:09 ET (6-May-2025 22:09 GMT/UTC)
Heat stroke poses a significant health risk, especially during extreme temperature conditions. While social media posts have demonstrated potential for detection of infectious diseases, its reliability remains a challenge. Now, researchers from Japan demonstrate the potential of combining social media posts and deep learning models for early detection of heat stroke risks. This approach opens up new possibilities for leveraging real-time data in event-based surveillance, enabling timely detection and response to heat stroke threats.
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