Hospitals worldwide are adopting AI-powered fever monitoring systems to improve patient care and reduce the spread of infectious diseases. These systems use thermal imaging cameras and machine learning algorithms to detect elevated body temperatures in real time, even in crowded settings like emergency rooms and airports.
A recent pilot study at Johns Hopkins Hospital demonstrated the system’s accuracy, with a 98% success rate in identifying febrile patients. The AI can distinguish between fever and other causes of elevated skin temperature, such as physical exertion or environmental factors. Additionally, the system integrates with electronic health records, allowing for immediate alerts to healthcare providers.
Beyond hospitals, this technology is being deployed in schools and workplaces to screen for contagious illnesses like influenza and COVID-19. Critics raise concerns about privacy and false positives, but developers argue that the benefits outweigh the risks. Future iterations may incorporate wearable devices for continuous fever monitoring at home.
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